Cardiac structural and valve interventions have remained surgical procedures for several decades. The ability to directly visualize the region of interest during surgery made imaging of these structures pre- and postsurgery a secondary tool to compliment surgical visualization. The last two decades, however, have seen rapid advances in catheter-based percutaneous structural heart interventions (SHIs). Due to the “blind” nature of these interventions, imaging plays a crucial role in the success of these procedures. Fluoroscopy is used universally in all percutaneous cardiac SHIs and helps primarily in the visualization of catheters and devices. However, success of these procedures requires visualization of intracardiac soft tissue structures. Due to its portable nature and rapid ability to show cardiac structures online, transesophageal echocardiography (TEE) has become an integral tool for guidance for all percutaneous SHI. Transcatheter aortic valve replacement—one of the earliest catheter-based procedures—while initially dependent on TEE, has largely been replaced by preprocedural cardiac CT for accurate assessment of valve sizing. Developments in echocardiography now allow live three-dimensional (3D) visualization of cardiac structures mimicking surgical anatomy during TEE. Besides showing actual 3D intracardiac structures, 3D-TEE allows visualization of the interaction of intracardiac catheters and devices with soft tissue cardiac structures, thereby becoming a “second pair of eyes” for the operator. Real-time 3D-TEE now plays an important role complementing multiplane two dimensional and biplane TEE during such interventions. In this review, we discuss the incremental role of 3D-TEE during various SHIs performed today. There has been enormous progress in catheter-based structural heart interventions (SHIs), with widespread use in the cardiology community. This has been made possible as a result of the development of new devices with improved performance as well as significant advances in the cardiovascular imaging field . FluorosThis 3D approach may improve the interventional cardiologist’s ability to interact with the TEE images during SHI. Among many advantages, 3D-TEE images can reconstruct a more realistic anatomic display of cardiac chambers and valves in real time and provide critical intraprocedural information . TherefoThe aim of this review is to analyze the current role of 3D-TEE imaging for SHI, focusing on the more common procedures that are FDA approved in the United States in which this rapidly evolving imaging technique can better assist the heart team in ensuring the best outcomes for patients. Non FDA approved devices currently undergoing phase three clinical trials including mitral and tricuspid valve replacement are also covered. Trans-septal puncture is a common procedure for SHI involving left-side cardiovascular structures. Some general rules need to be followed during this procedure; however, the majority of SHIs require a site-specific puncture for interventional success. Although trans-septal puncture is usually performed using only fluoroscopy, intraprocedural 3D-TEE could provide guidance for a more accurate targeted puncture and can be complementary to fluoroscopy and 2D-TEE imaging. Intracardiac ultrasound (ICE) may also be used to guide trans-septal puncture but requires the use of an additional catheter and offers limited 3D capability.The 3D technique could also help to avoid iatrogenic trauma, to ensure alignment of devices and catheters, and to secure adequate space to maneuver within the left atrium . AlthougRecommended 3D-TEE imaging reconstructions to display the interatrial septum correspond to fluoroscopy projections: in the anteroposterior projection, the septum is displayed in an oblique perspective corresponding to the 3D-TEE oblique perspective from the right atrium; the right anterior oblique projection corresponds to the 3D-TEE en face view from the right atrium—by using this view, interventional cardiologists can follow the catheter tip from the superior vena cava to the fossa ovalis; in the left anterior oblique projection, the side-on profile of the septum corresponds to the 3D-TEE lateral perspective .When the catheter is facing the interatrial septum, the puncture site is traditionally recognized by the tenting . This apRecently, there has been an expanding increase in the availability and utilization of transcatheter aortic valve replacement (TAVR) . The majThe aortic annulus is an ovoid shape that is less accurately sized by 2D-TEE imaging planes alone. A contemporary meta-analysis explored the precision of 3D-TEE in measuring aortic annular area, perimeter, diameter, and left ventricular outflow tract pre-TAVR . The corDuring the procedure, precise positioning of the bioprosthetic aortic valve is critical. Although fluoroscopy plays the main role, the use of 3D-TEE can help with confirming the correct placement during valve deployment and minimizing the need for contrast injection. The differentiation between the valve and the underlying balloon relies on the detection of an echo-dense, sharp-edged structure . In compAfter deployment, it is important to examine if complications have occurred, particularly prosthetic aortic regurgitation (AR). If 2D methods fail to accurately determine the severity of post-TAVR AR, color Doppler 3D volumes can help estimate the effective regurgitant orifice area (EROA) and the 3D color Doppler planimetry of the vena contracta area . This reFollowing valve deployment, it is also important to explore mitral valve (MV) morphology and function. A low deployment in the left ventricular outflow tract (LVOT) can cause impingement of the anterior mitral annulus and the anterior leaflet deriving in pseudo-stenosis or mitral regurgitation (MR), which can also be assessed with 3D-TEE if conventional parameters are inconclusive. However, there may be an improvement in pre-existing secondary MR following TAVR, predominantly related to changes in left ventricular hemodynamics and mitral leaflet tethering . A studyPost-TAVR complications involving the aorta or left ventricle are rare but could be potentially catastrophic . Real-tiThe complexity of the MV apparatus and the proximity of the transcatheter devices with other cardiac structures could lead to difficulties during MV catheter-based interventions . While cReal-time 3D-TEE imaging has fundamentally revolutionized the MV transcatheter edge-to-edge repair (TEER) procedure using MitraClip devices by facilitating the procedure, shortening the procedural time, and improving results. First, as already mentioned, successful trans-septal puncture requires a 3D understanding of the interatrial anatomy and its relationship to the surrounding structures. Obtaining an accurate view of the puncture site could be challenging using only 2D images, especially when the site is very posterior . Thus, 3The maneuvering of the delivery system into the left atrium and its advancement toward the MV could be monitored by using 3D-TEE images from an oblique perspective of the interatrial septum. This view displays the relation between catheters, the atrial wall, and the interatrial septum, thus allowing the operator to maneuver the catheters without injuring cardiac structures [The correct orientation of the clips in a perpendicular manner to the coaptation line is critical for the intervention success and adequate leaflet grasp. This requires visualization of the MV on the short-axis plane. Two-dimensional TEE can only show this view in the transgastric plane and oftentimes may not be able to show this view in the correct anatomical plane or only show the view limited by gastric air. Real-time 3D imaging of the MV with the probe at the mid esophageal level provides a superb view of the entire MV from the atrial perspective, including anterior and posterior leaflet scallops, anterior and posterior commissures, and mitral annulus. This 3D-TEE view enables imaging of the clips’ arms and the MV coaptation line; therefore, it should be used to ensure that clips are perpendicular to the coaptation line [Only a limited number of 3D-TEE views are normally required for the intraprocedural guidance; meanwhile, for 2D-TEE, various views are usually needed to establish the adequate position of the clip(s). Additionally, 2D-TEE can be inaccurate in locating the tip of the catheters and its spatial relationship with the coaptation line while, with 3D-TEE, the spatial location of catheters in relation to surrounding structures is easier to comprehend . TherefoIn a series of 26 patients, Altiok et al. demonstrated that 3D-TEE provided critical additional information compared with 2D-TEE in various central steps of the TEER intervention. Those steps included the guidance and maneuvering of the catheters, the accurate positioning and alignment of the first clip, the confirmation of correct grasping location, and the proper positioning of any additional clips, if required . Real-tiPercutaneous annuloplasty or leaflet repair techniques may not be sufficient to eliminate MR in some scenarios depending on native valve characteristics . TranscaHowever, TMVR procedures are highly challenging due to several factors. These include the complex geometry of the mitral apparatus, the large size of the mitral annulus, the relative lack of calcification (which is a landmark used for fluoroscopic guidance), and the need to protect neighboring structures such as the coronary sinus, coronary arteries, and the LVOT . In ordeFor preprocedural planning, 3D-TEE datasets centered on the MV can be reconstructed using different planes to perform thorough quantifications of the mitral annulus. One study confirmed the clinical feasibility and accuracy of the assessment of the MV geometry with 3D-TEE when compared to CT measurements . In addiRegarding the use of intraprocedural TEE, 2D- and 3D-TEE guidance could be important for successful valve deployment. The mid-esophageal short-axis and bicaval views allow us to display the interatrial septum and maneuver the catheters; the mid-esophageal commissural view can help achieve correct medial–lateral positioning of the device; the mid-esophageal long-axis view is useful to estimate the anterior–posterior positioning of the device; lastly, a transgastric short-axis view can evaluate coaptation of leaflets .Postdeployment, 3D-TEE can be useful to verify the proper position and function of the device, to identify and quantify the severity of residual MR, and to detect procedural complications.Perivalvular dehiscence is an undesired complication that may happen after a prosthetic valve replacement procedure, more frequently affecting patients with mechanical mitral replacements. Transcatheter leak closure has emerged as a viable alternative to surgical redo procedures, especially in high-risk patients. However, these percutaneous procedures are usually complex and detailed imaging guidance is required ,33.The 3D multiplane reconstruction can be particularly useful to confirm the location and extent of periprosthetic regurgitation. Intraprocedural 3D-TEE guidance may provide critical information to the interventional cardiologist when crossing the dehiscence, as imaging can confirm the guidewire position across the perivalvular defect. In particular, the use of multiplane 3D images can be important in cases with severe calcification, sinuous dehiscences, or complex locations . The en Traditional 2D-TEE has several limitations in the assessment of dehiscences, including the interference of prosthetic material, sutures, or calcifications. However, the most challenging one is its inability to delineate the complete extent of periprosthetic dehiscences, which can be multiple and frequently anatomically complex . In thisFusion between TEE and fluoroscopy imaging may simplify the closure procedure, particularly in cases of radiolucent prosthetic valves . By compOne study investigated the clinical value of 3D-TEE for the catheter-based closure of paravalvular leaks in mitral prosthesis. This study showed no significant disagreement between 2D- and 3D-TEE color flow Doppler for the location of each leak, the vena contracta width, and the reduction in the paravalvular leak vena contracta width. However, only 3D-TEE had the ability to detect the decrease in the effective orifice circumferential length of the leak, suggesting that this technology could provide unique and additive information in this scenario .A study of ten patients with persistent mitral leak following transcatheter closure demonstrated that 3D-TEE was able to confirm the location and number of the residual leaks, along with their morphological characteristics . Additionally, 3D-TEE imaging also helped identify the exact location of the devices, allowing improved comprehension of the causes underlying the intervention’s failure .In a study of 166 patients with either mitral or aortic paravalvular leaks, TTE, TEE, and 3D printing were utilized for the preoperative evaluation of the defects. Among the included cases, 68 used preoperative TEE and 3D printing and showed advantages when compared with traditional TEE guidance, with a decrease in interventional and fluoroscopic times .Catheter-based treatments of tricuspid regurgitation (TR) are becoming a viable option for patients who are at high risk of surgical procedures. Therefore, different devices with diverse mechanisms of action have been developed . SpecifiThe 3D multiplane imaging could be crucial during these complex cases. The 3D multiplane mode is usually most useful from the mid-esophageal commissural views at the site of the TR jet to display the four-chamber view, as well as from the transgastric short-axis tricuspid valve (TV) view. These views display the leaflet grasping view, which is critical to evaluate feasibility and to decide the final transcatheter device placement. These views also provide information to determine the TR mechanism, orifice size, septal leaflet length, and septal leaflet curling . In addiLastly, 3D-TEE multiplane reconstructions can help with the final evaluation of the position of the device following placement and 3D color Doppler should assess the presence and magnitude of potential residual jets. For some particular devices, transgastric views with 3D reconstruction of the right ventricle anchor path and landing zone may be important .With the FDA approval of left atrial appendage (LAA) catheter-based occlusion devices, the use of cardiovascular imaging for real-time assessment of the LAA orifice area has become critical for accurate sizing and placement of devices . PreviouDuring transcatheter occlusion procedures, the 3D-TEE technique is usually used to ensure the proper position of the catheter by using an en face view of the LAA orifice [Pulmonary vein stenosis is considered an uncommon disease with a challenging diagnosis and potential undesired consequences if left untreated. Currently, injury from radiofrequency ablation for atrial fibrillation has become the main cause of this condition, and transcatheter intervention is the most common therapeutic approach. When this diagnosis is suspected, multimodality imaging methods are usually required for confirmation .Angiography is traditionally utilized to locate pulmonary veins stenosis. Using only this technique, it could be difficult to easily identify occluded pulmonary veins; however, 3D-TEE could help locate them. The use of 3D-TEE during pulmonary vein interventions provides a real-time assessment of pulmonary veins anatomy along with a better understanding of the spatial relationships between cardiac structures . These aAnother scenario for the potential use of 3D-TEE is to complement other imaging methods during anatomy-driven catheter-based radiofrequency pulmonary veins ablation . A 3D-TEThe use of intraprocedural 3D-TEE has been also proposed in patients with Scimitar syndrome, characterized by an anomalous venous return from the right lung directly into the inferior vena cava. Full-volume 3D-TEE imaging can illustrate the abnormal pulmonary vein entrance into the inferior vena cava and can help identify the orientation of the scimitar vein with respect to the hepatic veins and the inferior vena cava . This caFluoroscopy has been the traditional method for intraprocedural guidance in SHI and has its own strengths. Wires, devices, and catheters for SHI have been designed and developed to be radiopaque to maximize fluoroscopic guidance, while these medical tools usually create undesired artifacts in echocardiography imaging. Moreover, in contrast to echocardiography, fluoroscopy displays a larger field of view that allows interventional cardiologists to follow and visualize long segments of catheters. The temporal resolution of fluoroscopy is also appropriate to maneuver the catheters and devices, while a major limitation of 3D imaging is its poor temporal resolution, which is related to the increased use of data points to generate 3D images . TherefoAs outlined in this review, multiplane 3D-TEE imaging can offer an interesting number of advantages when utilized in a complementary manner to fluoroscopy during SHI. Soft tissues of critical cardiac structures are transparent to radiography; so, echocardiography is of paramount importance for an accurate anatomical assessment of the targeted structures. When comparing the more novel 3D approach with traditional 2D techniques, real-time multiplanar 3D-TEE imaging, and particularly en face views, supply additive and more appropriate guidance of catheter manipulation by providing improved imaging and comprehensive information about the spatial positioning of wires and devices and their relationships with surrounding cardiac structures. The multiplanar perspective of 3D-TEE allows the use of several imaging planes specific to each procedure with no need for several changes in probe position. This may lead not only to more accurate technical outcomes but can also help in reducing complications and suboptimal deployments during SHI. Additionally, 3D-TEE techniques can help shorten the duration of procedures, thus reducing the volume of contrast and radiation exposure both for the patients and the heart team.New technologies are continually being developed in the field of cardiovascular imaging. ICE has been proposed as an alternative for TEE guidance for SHI. However, this method is not without disadvantages, including costly single-use catheters, the potential interference between the catheter and temporary/permanent pacemaker leads, limited 3D evaluation , and smaller field of view, making it challenging to appropriately display structures far away from the right atrium . AdditioAs the use of 3D-TEE is becoming more frequent for cardiac SHI, the applications of this technique are now expanding to other percutaneous interventions. It has been proposed that 3D-TEE techniques could also have a role in planning or guiding percutaneous aortic procedures , as the However, potential barriers exist for the general implementation of 3D-TEE imaging in the catheterization laboratory. First, interventional cardiologists are more familiar with fluoroscopy guidance than with echocardiography imaging for SHI. As 3D-TEE is becoming a useful complementary tool during SHI, training programs for interventional cardiologists could better include the use of this novel technique. Moreover, images obtained from fluoroscopy and echocardiography are usually displayed on separate screens, thus limiting the understanding of the spatial relationships between cardiac devices and cardiovascular structures. In this sense, further advances to refine the management of digital images would allow researchers to improve the creation of fusion images from both fluoroscopy and TEE. This fusion between two imaging modalities in one 3D space and time will create sophisticated images that can be shown on a single screen and better utilized by the cardiologists. Another frequent limitation with 3D images is related to the artifacts that may occur when the ultrasound beam intersects catheters and devices. Additional limitations include the lack of a standardized core curriculum for SHI imagers and the lack of unified guidelines for the use of 3D-TEE during SHI; however, efforts are being made to establish a current state-of-the-art regarding the use of imaging techniques during SHI, including the use of new imaging technologies . Lastly,The use of 3D-TEE imaging during SHI has several benefits, including an easier localization of the anatomical structures of interest and devices, an easier navigation inside the heart chambers, and a more precise localization of the landing zone of devices. As the use of this technology is expected to extensively increase during transcatheter interventions, appropriate and consistent recommendations for intraprocedural guidance are critical. Future large-scale prospective studies are still needed to demonstrate that the use of 3D-TEE in this scenario generates practical advantages such as shortening of the procedural time, increased procedural success, reduction in procedural complications, and reduced radiation and contrast exposure.


Influenza vaccination is the key to prevent influenza-related disease, especially among high-risk populations. However, influenza vaccine uptake in China is low. This secondary analysis of a quasi-experimental trial aimed to understand factors associated with influenza vaccine uptake among children and older people stratified by funding context.A total of 225 children (aged 0.5-8 years) and 225 older people (aged 60 years or above) were recruited from three clinics  in Guangdong Province. Participants were allocated into two groups based on funding contexts: a self-paid group  in which participants paid full price for their vaccination; and a subsidized group  in which varying levels of financial support was provided. Univariate and multivariable logistic regressions were conducted stratified by funding contexts.Overall, 75.0% (225/300) of participants in the subsidized group and 36.7% (55/150) in the self-paid group got vaccinated. Older adults had lower vaccination rates than children in both funding groups, while both age groups showed much higher uptake in the subsidized group than in the self-paid group . In the self-paid group, having prior influenza vaccination history of children  or older people  was associated with increased influenza vaccine uptake compared to those who had no prior vaccination experiences in the family. While in the subsidized group, participants who got married or lived with partners  had lower vaccination uptake than single ones. Trust in providers’ advice , perceived effectiveness of the vaccine , and experienced influenza-like illnesses in the family in the past year  were associated with higher vaccine uptake.Older people had suboptimal vaccine uptake compared to children in both contexts and need more attention to enhance influenza vaccination. Tailoring interventions to different vaccine funding contexts may help improve influenza vaccination: In self-paid context, motivating people to accept their first ever influenza vaccination may be a promising strategy. In subsidized context, improving public confidence in vaccine effectiveness and providers’ advice would be useful.The online version contains supplementary material available at 10.1186/s12879-023-08145-8. Influenza is a respiratory infectious disease causing 300,000 to 500,000 deaths worldwide each year . In ChinInfluenza vaccination is the most effective way to prevent infection and reduce influenza-related disease burden . SystemaVaccination-associated user fees could be a barrier and public funding to lower costs can increase influenza vaccination uptake , 13. PubFactors influencing vaccine uptake are multi-faceted. Previous systematic reviews identified sociodemographic, knowledge, attitudes , experiential and contextual factors as barriers and facilitators of influenza vaccine uptake –24. MostThis is a secondary data analysis of a parent quasi-experimental study  in which the effectiveness of a pay-it-forward intervention in improving influenza uptake in children and older people was assessed against a standard-of-care arm. Individuals in the pay-it-forward arm received free vaccine pre-paid by others in the community and offered the individual an opportunity to donate voluntarily at any amount to support subsequent people to receive the same service . An addiThe parent intervention study took place between September 2020 to February 2021 in Guangdong Province of Southern China where influenza is prevalent throughout the year . The stuChildren and older people were included as our study populations and combined for analysis. There are three reasons for this:1) both children and older adults are at-risk populations of influenza infections and priority groups of vaccination in China ; 2) inflThe intervention study used a quasi-experimental design and included three arms: a standard-of-care arm (i.e. participants had to pay the standard market price for their vaccine), a free-of-charge arm  and a pay-it-forward arm . Participants in all three arms received introductory pamphlet about influenza and vaccination. The intervention study aimed to compare the effectiveness between pay-it-forward and standard-of-care in influenza vaccine uptake among children and older people, with the free vaccination arm not being powered to test the differences and serving the purpose for costs comparison . The payA non-random approach was adopted for participant recruitment in this trial. Participants recruited were chronologically allocated into the specified study arms. Detailed timeline of participant recruitment in each study arms at each site can be found in the published work of the parent study . Each stParticipation in the study was voluntary and anonymous. All participants were asked to complete a self-reported questionnaire (Appendix B1) after being introduced the intervention. Administrative data recorded by the project staff included the number of eligible people invited, number of individuals who participated and completed a survey, and number of participants who received a vaccination. Data source for secondary analysis consisted of independent variable information from self-reported questionnaire and outcome variable information from administrative data.The three study arms were categorized into two groups to reflect varying funding contexts in the Chinese setting: self-paid group  and subsidized arm . We had practical and statistical considerations for combining pay-it-forward arm with free-of-charge arm.First, a combined subsidized group consisting of a free arm (vaccine costs were fully covered) and a voluntary pay-it-forward arm  could give a simplified practical understanding of the complex vaccine funding policy in China. It also allows us to identify associated factors of influenza vaccine uptake in a context where some level of public financial support is available, in comparison to a context where people self-pay for vaccination.Second, the donations in the pay-it-forward arm were made on a complete voluntary basis and did not conflict with the subsidized strategy. Free vaccine was at first given to people in the pay-it-forward arm, they were then being asked whether they would like to donate any amount of money. Additionally, results of analysis from the parent study support the homogeneity of pay-it-forward and free-of-charge arm from an economic point of view. The costs per person vaccinated in the pay-it-forward arm (USD 40.33) were close to those in the free vaccine arm (USD 40.92) .Third, statistically, the sample size calculation was not powered to test differences between free-of-charge and the other two arms in the parent study. The free-of-charge arm only served a purpose for costs evaluation . AdditioAnderson’s Behavioral Model has been used extensively to understand health service utilization in different health care settings . We adapFigure Descriptive analysis was performed to generate frequency distributions of influenza vaccine uptake among children and older people. Differences in sociodemographic characteristics between intervention groups were tested using Pearson’s χ2 test.We conducted univariate and multivariable logistic regressions for participants in the self-paid and subsidized group respectively, to examine factors influencing Influenza vaccination uptake in different funding context. The binary outcome was ascertained by administrative data and defined as receiving an influenza vaccine or not. All independent variables selected based on the adapted Anderson’s Behavioral Model. Age, sex, and intervention status  were determined as prior confounders. After the adjustment for prior confounders, each explanatory variable with a significance level of p < 0.2 had a chance to enter the multivariable logistic regression models. Multivariable regression was developed based on the backward stepwise strategy. To avoid sparse data according to approximately ten events per variable , a backwEthical approval for the parent quasi-experimental study was obtained from the institutional review boards at the London School of Hygiene & Tropical Medicine (Ref: 19100) and the Zhuhai Center for Disease Control . This secondary study was approved by the Research Ethics Committee of the London School of Hygiene and Tropical Medicine (Ref: 25292).Characteristics of the participants by study groups are presented in Table The overall influenza vaccine uptake was 62.2% (280/450), with 36.7% (55/150) of participants in the self-paid group and 75.0% (225/300) in the subsidized group. Vaccine uptake among children and older people are shown in Appendix Figure C1. For both participant types, vaccination uptake in the subsidized group is higher than that in the self-paid group . Overall, influenza vaccination rate in subsidized group is nearly 6 times  of that in self-paid group according to the multivariable logistic analysis  are shown in Table Multivariable regression analyses of the subsidized group Table  also sugThere is limited understanding of barriers and facilitators of influenza vaccine uptake in LMICs , 26. ThiParticipants in the self-paid group were less likely to be vaccinated than those in the subsidized group. This finding is supported by existing literature that reducing out-of-pocket expenses is an important facilitator for influenza vaccine uptake , 37–39. Our study also found that older people had significantly lower vaccine uptake than children. It is far below the World Health Assembly (WHA) target of 75% vaccine coverage among older people . This maIn the subsidized vaccine group, positive perceptions and experience of influenza-like illness in the family played an important role in vaccine uptake. This is consistent with previous studies that showed positive impacts of participants’ confidence in vaccine effectiveness , 20, 28 In the self-paid group, previous vaccination experience was identified an associated factor with vaccine uptake. This is supported by previous studies , 19, 20.Our study findings have implications for tailoring strategies for influenza vaccine programs with varying levels of public funding support. In places where limited funds are provided and people self-pay for influenza vaccine services, messages and strategies targeting improved initiation of the influenza vaccination  may be a promising direction. In regions where subsidized vaccines are available, in addition to motivating new users, additional efforts to improve public confidence in vaccine effectiveness and healthcare workers, and messages to change people’s self-perceived low risks of influenza infection are needed to enhance uptake. Additionally, compared to children, older adults are worth more attention, especially in an aging societyThis study also has limitations. The data were collected at one given point in time without follow-ups and this has limitations to examine causality. First, future investigation can include longitudinal evaluation of influenza vaccine uptake in the next winter season, and our study findings provide important evidence base to support future tailored vaccine programs targeting improved uptake. Second, selection bias may result from the participant recruitment procedure. People recruited in attendance to primary care were more likely to have better health literacy. Additionally, lockdown restrictions after the COVID-19 outbreak have raised barriers to accessing primary healthcare, especially for those less-educated, deprived and unemployed groups . TherefoInfluenza vaccination disparity was found between older people and children in both subsidized and self-paid vaccine circumstances. Tailored interventions, particularly among older people, should be developed. Motivating new users to initiate influenza vaccination is an important step in context of self-paid vaccination. Addressing public confidence in vaccines/healthcare providers and people’s self-perceived low risks of influenza infection would be a promising direction for further improvement, and this may be particularly true for places that already provide free or subsidized influenza vaccines to their local populationsBelow is the link to the electronic supplementary material.Supplementary Material 1


The MMSE score lowered on average by 1.7 points/year, independently of COVID-19, but it lowered twice faster in those who had COVID-19 . BADL and IADL indexes lowered on average less than 1 point/year, independently of COVID-19 occurrence. Patients who had COVID-19 had a higher incidence of new institutionalization than those who did not have the disease . Conclusions: COVID-19 had a significant impact on cognitive decline and accelerated MMSE reduction in elderly patients with dementia.Introduction: Coronavirus disease 2019 (COVID-19) may affect the cognitive function and activities of daily living (ADL) of elderly patients. This study aimed to establish the COVID-19 effect on cognitive decline and the velocity of cognitive function and ADL changes in elderly patients with dementia followed up in an outpatient memory care facility. Methods: In total, 111 consecutive patients  with a baseline visit before infection were divided into those who had or did not have COVID-19. Cognitive decline was defined as a five-point loss of Mini-Mental State Examination (MMSE) score and ADL comprising basic and instrumental ADL indexes . COVID-19 effect on cognitive decline was weighted for confounding variables by the propensity score, whereas the effect on change in the MMSE score and ADL indexes was analyzed using multivariate mixed-effect linear regression. Results: COVID-19 occurred in 31 patients and a cognitive decline in 44. Cognitive decline was about three and a half times more frequent in patients who had COVID-19 (weighted hazard ratio 3.56, 95% confidence interval 1.50–8.59,  Several studies suggested that in elderly patients with cognitive impairment, coronavirus disease 2019 (COVID-19) is associated with cognitive function decline and worsened activity of daily living (ADL) , dissectThe social isolation imposed to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has deprived patients with cognitive impairment of the care and support necessary to ensure adequate mental, physical, and social well-being, conditions that are essential to maintain cognitive functions and preserve normal ADL in elderly patients with cognitive impairment ,5. It haEvidence supports both the direct and indirect effects of COVID-19 on cognitive function. COVID-19 was associated with risk factors that can accelerate the decline in cognitive function and ADL such as hospitalization, prolonged bed rest, and use of medical therapies . In addiAssessing the preliminary effect of COVID-19 on cognitive function and indexes of ADL over time is also essential to design appropriate-sized prospective studies on the short- and long-term consequences of COVID-19 in patients with pre-existing dementia. For this purpose, this study aimed to explore the COVID-19 effect on cognitive function, ADL indexes, and new institutionalization in patients with dementia followed up in an outpatient memory care facility in Trieste city in northeastern Italy. In this location, the pandemic burden on older people was dramatic, and sensitivity to cognitive decline prevention was high ,15. Pati2 at initial assessment and calculated with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [Consecutive outpatients who were evaluated at the Memory Care Facility of the Department of Continuity of Care in Trieste were included in this retrospective longitudinal study. The inclusion criteria were all sexes, age 65 years or higher, any diagnosis of dementia, and at least a baseline and a consecutive follow-up visit. All the follow-up visits were performed during the COVID-19 pandemic, whereas the baseline visits were performed before or during the pandemic period. Specifically, we included patients whose first follow-up visit was during the pandemic and collected information about the precedent baseline visit whenever it was performed. Usually, patients received a 3- or 6-month follow-up to check therapy control or changes in clinical symptoms depending on the severity of dementia. A yearly follow-up was prescribed for clinically stable patients. When a patient missed a follow-up visit, she or he received advice to reserve a new control. Visits at the facility were standardized and conducted by an expert geriatrician who completed clinical and multidimensional evaluations. The exclusion criteria were a baseline Mini-Mental State Examination (MMSE) score of lower than 5 points or a lack of complete data. In this cohort of patients, the cases were those patients who were infected with SARS-CoV-2 and developed COVID-19 after the baseline visit, whereas the controls were those patients who did show signs of SARS-CoV-2 infection during the same period and were not tested or tested negative. The occurrence of COVID-19 and hospitalization for any cause during the study period were assessed by directly interviewing the patient or its caregiver, checking medical records, or contacting the general practitioner. All the patients who had been examined in the facility during the pandemic had to test negative before entry. Hospitalization for any cause was defined as any access to the hospital through the emergency department because of an acute illness, including severe COVID-19. Paucisymptomatic patients were not hospitalized. Patients without symptoms of SARS-CoV-2 infection were not tested unless they were contacted with COVID-19 cases. The diagnosis of SARS-CoV-2 infection relied on the positivity of two rapid antibody or genomic molecular tests, according to the World Health Organization guidelines . In eachequation . Parkinsequation  and confData were derived from the routine clinical management of patients performed at the memory care facility according to good clinical practice and under the Declaration of Helsinki principles. A generic informed consent form with the possibility of analyzing personal data after anonymization for research was signed by each patient or their caregiver when the patient could not give informed consent at the first contact with the center. The Institutional Review Board of the University of Udine approved this study (protocol number 153/2022), stating that no additional informed consent was needed for the retrospective analysis of data. The diagnosis of dementia was established by the criteria proposed in the Diagnosis and Statistical Manual of Mental Disorder 5th edition (DSM-V), and dementia was differentiated into the following forms: Alzheimer’s disease, vascular dementia, mixed, dementia secondary to Parkinson’s disease, dementia with Lewy bodies, and frontotemporal dementia ,21. Becat-test for the variables normally distributed. Wilcoxon’s test was used to assess differences in the continuous variables that were not normally distributed. The difference between proportions was assessed using Fisher’s exact test. Continuous variables were summarized as mean ± standard deviation when the variable was normally distributed or as median (interquartile range IQR) when it was not. Normal distribution was assessed by looking at the histogram of variable distribution and confirmed with the Shapiro–Wilk test. Categorical variables were summarized as counts and percentages. The variables were grouped according to the occurrence of COVID-19 or a significant cognitive decline (reduction in the MMSE score of at least 5 points). The difference between means was assessed using Student’s p) lower than 10% at the univariate Cox regression analysis  and were estimated using the nonparametric covariate balancing propensity score method according to Fong et al. [The effect of COVID-19 on the time to cognitive decline was assessed using the Cox proportional hazard regression and expressed as a hazard ratio (HR) with a 95% confidence interval (CI). To account for unbalanced confounders, the HR was corrected and reported as weighted HR (wHR) with a 95% CI. Weights corrected the confounding variables that predicted either COVID-19 or significant cognitive decline by a probability .The effect of COVID-19 on the yearly change in the MMSE score and ADL indexes was assessed through linear mixed-effect regression including the interaction between COVID-19 and follow-up time. The effects of COVID-19 on the MMSE score and ADL indexes were adjusted for those variables that differed between patients who had or did not have COVID-19, with a In this study, 111 consecutive patients were included after having excluded 5 patients because of a baseline MMSE score lower than 5 points (3 patients) or incomplete data (2 patients). The baseline characteristics of the cohort are summarized in p = 0.004). At the baseline, the patients who had COVID-19 had a higher proportion of diabetes and institutionalization, lower MMSE scores, BADL and IADL indexes, and shorter follow-up times than controls . The patThe linear mixed-effect regression analysis unadjusted for confounders showed that the MMSE score lowered on average by 1.7 points each year, independently of COVID-19. There was an interaction between COVID-19 and follow-up time in that the patients who had COVID-19 had 1.6 points relatively greater reduction in their MMSE score each year than those patients who did not have the disease A. The MMWe defined a significant cognitive decline as the reduction of at least five points in the MMSE score, according to Doody et al. . An MMSEIn this study, having had COVID-19 predicted a faster cognitive decline than not having had the infection. Our results are in line with the previous findings summarized in the meta-analysis of Crivelli et al. . Our stuIn a larger prospective study by Liu et al. on over 3000 older patients and their uninfected spouses as controls, COVID-19 was associated with a progressive cognitive decline at 6 and 12 months after recovery . The autBased on previous studies, it would be expected that patients with severe COVID-19 may improve their cognitive functions in the long term ,31. ThisIn this study, the MMSE score and ADL indexes were lowered on average in the cohort of patients, independently of COVID-19 occurrence. This observation was expected since all of our patients were subjected to the same social restriction imposed by the National Authority, and social restriction has been shown to impair the performance of the elderly, independently of COVID-19 ,35,36. CAlthough in our study, the MMSE score declined independently of COVID-19, the MMSE score was lowered about twice faster in patients who had COVID-19. To justify this observation, it should be considered that SARS-CoV-2 infection has been associated with reduced brain size and lower gray matter thickness, blood–brain barrier damage, the inflammation of the brain tissue, and increased incidence of cerebrovascular ischemic and hemorrhagic events, encephalitis, and other metabolic brain abnormalities. All these events contribute to cognitive dysfunction and the development of dementia ,38,39. IOther important limitations of this study were the following factors: First, the sample number of this study was small. During the pandemic, access to the memory care facility was limited because of home constraints and healthcare resources shifting to COVID-19 care. Therefore, fewer patients received memory care visits, and data availability was limited. Second, some baseline visits were performed years before the pandemic, with the risk of bias because of the different treatment periods. However, the level of assistance in the memory care facility is standardized, and it is independent of the period when the visit is performed. In addition, since all follow-up visits were performed in the pandemic period and the median time between the visits was similar in patients who had or did not have a significant cognitive decline, it means that for the outcome of this study, the different periods of baseline visits were not significant. Third, the retrospective inclusion of consecutive patients determined two groups of patients who had or did not have COVID-19 that were not homogenous. For example, the patients who had COVID-19 showed a trend of lower cognitive and ADL functioning and had higher medication use at the baseline. Therefore, as expected, those who contracted the infection already appeared as a frailer group . We mitiIn conclusion, this study showed that COVID-19 was an important determinant of cognitive decline and accelerated cognitive dysfunction in elderly patients with pre-existing dementia followed up in an outpatient memory care facility. The clinical relevance of this observation was highlighted by the increased incidence of new institutionalization in patients with cognitive decline. Intensive rehabilitation and strict follow-up at memory care facilities might mitigate such a cognitive decline, but further long-term prospective studies should clarify this point.


The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for the high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection and the successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled the testing of over 8000 pooled samples per day and provided results for over 2 million samples. The automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results, and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turnaround-time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response. The novel coronavirus now known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China at the end of 2019 and spread worldwide, causing an unprecedented pandemic . InfectiUniversity settings offer many opportunities for interactions of groups of individuals that originate from across the globe. University campuses offer many shared spaces designed for a variety of academic, dining, and residence purposes and experiences. Additionally, social gatherings are abundant. These features complicate the control of SARS-CoV-2 transmission on a university campus. Recognizing the characteristics of viral transmission and the unique environment of the university campus, a surveillance testing program was designed at Cornell University during the summer of 2020. A key aspect of this program was the frequent testing of the entire university community including asymptomatic individuals for SARS-CoV-2. We reasoned that on-campus SARS-CoV-2 testing would enable the university to (1) rapidly identify individuals infected with SARS-CoV-2 so they could be isolated and/or obtain prompt medical attention; (2) perform contact tracing to rapidly identify potential pre-symptomatic or asymptomatic secondary cases and limit further spread; (3) provide SARS-CoV-2 incidence case counts and the prevalence of positive samples for the campus community and local public health authorities; and (4) reveal the dynamics of SARS-CoV-2 transmission within the university community.As a central pillar of the Cornell surveillance program, we established a high-throughput SARS-CoV-2 testing laboratory, the Cornell COVID-19 Testing Laboratory (CCTL). The objective of the CCTL was to offer pooled testing with minimal result turnaround times to enable the rapid isolation of infected individuals and quarantine contacts. To meet that objective, our workflow needed to accommodate the testing of pooled or individual samples simultaneously. Surveillance samples were pooled before testing to maximize the testing capacity and decrease the cost of testing. Individual testing was included in the laboratory workflow to deconvolute SARS-CoV-2-positive pools and identify positive individuals, to test specimens for contact tracing efforts, to test specimens collected from symptomatic individuals, or for testing when the probability of a sample being positive was high enough to limit the advantage of pooling. The Cornell COVID-19 surveillance schedule and other public health measures taken have been described elsewhere .Given the anticipated high-volume testing needs (8000 samples per day), we identified the steps in the workflow that were the most time- and labor-intensive and implemented automation. Accessioning thousands of specimens per day is a time-consuming step. Pooling specimens is both time- and labor-intensive. Manually labeling runs with specimen identifiers is another time-intensive step where errors could be introduced. Manual sample and reagent transfer between 96-well plates are repetitive steps with ergonomic stressors. All these steps were targeted for automation using either robotics or electronic data transfer methods.The premise of high-throughput pooled testing posed significant information technology (IT) challenges. Once the testing strategy and testing workflow were designed, our IT team developed efficient software applications to support the workflow without the need for users to switch between different applications or to access the laboratory information management system (LIMS). Customized application software and scripts were essential to minimize hands-on input and achieve a streamlined automated workflow.Another important consideration was the selection of the SARS-CoV-2 assay to be used at CCTL. An RT-PCR that offered high sensitivity to allow pooling and high accuracy to limit the number of repeated tests was optimal. To reduce the risk of delays due to a potential testing reagent shortage, two RT-PCR tests were selected for the initial evaluation and validation of the workflow: (1) the EZ-SARS-CoV-2 assay developed by Tetracore Inc.  and (2) the TaqPath COVID-19 Combo Kit Multiplex Real-Time RT-PCR assay   which haConsidering the short time frame available to launch the laboratory, the workflow incorporated experienced faculty and staff from the Animal Health Diagnostic Center (AHDC)—a Level 1 member of the National Animal Health Laboratory Network (NAHLN)—and PCR instrumentation routinely used at AHDC for the testing of animal clinical samples. Similarly, the IT staff and application developers were familiar with the needs specific to diagnostic testing. CCTL was operated in partnership with Cayuga Medical Center (CMC) as they provided critical expertise in the regulations governing human diagnostic testing, quality control, and human laboratory testing operations. Herein, we describe the workflow that was designed and implemented to meet the considerations above and to optimize the laboratory’s performance.A unidirectional workflow was designed for high-throughput SARS-CoV-2 testing to support Cornell University’s SARS-CoV-2 surveillance program. Five rooms in a BSL-2 laboratory space were designated to separate and isolate specific steps in the testing process: (1) specimen receiving, processing, and pooling; (2) nucleic acid extraction; (3) RT-PCR mastermix preparation; (4) RT-PCR setup; and (5) a large room with discrete benches dedicated for extraction reagent preparation, real-time PCR instruments, and a computer area for app usage and result analysis. In brief, the workflow began with specimen receipt and proceeded to automated accessioning into LIMS and sample transfer and pooling using Biomek i5 liquid handler automated workstations . Sample Our previous study determined that anterior nares (AN) swab specimens were appropriate for SARS-CoV-2 diagnostic testing, whether obtained from symptomatic individuals or asymptomatic individuals for surveillance purposes . MultiplSpecimens were delivered to the CCTL in 5 mL conical tubes and identified with unique barcode identification labels. Staff wore enhanced PPE exceeding the requirements for BSL-2 when inspecting, processing, and transferring specimens. Specimens were inspected to confirm that each tube contained either one swab with VTM or saliva, with a single legible barcode label. Swab specimens were refrigerated (2–8 °C) upon arrival in the laboratory and were only removed during processing. For processing, swab specimen tubes were placed in racks and vortexed at 2200 rpm for 5–10 s using a Fisherbrand™ Microplate Standard Vortex Mixer , then allowed to sit for 5–15 min at room temperature (RT).g and 25 °C for 5 min. If the saliva volume was at least 1.5 mL, it was transferred using the Biomek i5; if the volume was less than 1.5 mL, it was transferred manually and tested individually. Saliva specimens were kept at RT or refrigerated (2–8 °C) until processing and then refrigerated until disposal. Saliva specimens were subjected to centrifugation at 1855× Prepared specimen tubes were placed in Biomek tube racks so that the specimen barcode was visible between the rack position barcodes .Specimens were transferred from 5 mL collection tubes to 96-deep-well plates for nucleic acid extraction using Biomek i5 automated workstations with high-efficiency particulate air (HEPA) filters . Biomek software version 5.1, Biomek Method Launcher version 3.2, and Data Acquisition and Reporting Tool (DART) 2.0 software were provided with the workstation (Beckman Coulter Life Sciences). The Biomek i5 automated workstations were operated inside benchtop biocontainment enclosures  for an additional layer of biosafety.Once the specimens were ready to be scanned and pooled, the Create Accession Application (app) was opened. The appropriate submission source, specimen collection date, specimen type, and number of total specimens for the run were entered. The app automatically created the accession and records for each sample in the LIMS database. The sample identifications were initially created as an auto-incrementing number in the LIMS. The app also printed a set of barcoded labels with the run’s accession number. One accession label was placed on the 96-deep-well sample plate and the rest of the accession labels accompanied the specimen plate through the workflow. The labeled 96-deep-well sample plate was placed on the Biomek deck in preparation for sample transfer and pooling.From the Biomek launcher software, the appropriate method was selected for the run . The methods scripts were custom-designed using Python scripts and consisted of step-based workflows used by the Biomek liquid handler to process the samples. The first step was to scan the barcode label on the 96-deep-well sample plate, identifying the accession number that was created at the beginning of the workflow. Initiating and running the Biomek method step launched the Python script, which used the scanned barcode to connect to the LIMS database and determine the number of samples to be pooled or transferred. The Python script then updated the DART reports generated using Biomek. The reports specified the number of samples to be processed and which samples would be pooled into each well of the 96-deep-well plate. A full plate had 465 samples, pooled in groups of 5 samples per well (185 µL of each sample), thus creating 93 pools. If there were fewer than 465 samples to be scanned and tested that could not be evenly distributed into pools of 5, the final pool would have either 2, 3, or 4 samples. If the final pool was determined to have just one sample, then the script directed that the penultimate pool would have four samples and the final pool would have two samples. During the validation of this assay, the limit of detection (LOD) was determined to be 250 genome copies per mL and the diagnostic sensitivity for a pool of 5 samples was 93% .Next, Biomek tube racks with specimen tubes were loaded into the Biomek. The Biomek tube racks also had position barcode labels that identified the location of each tube . As the The Biomek i5s used in our workflow were equipped with a Span-8 pipette head that could transfer 8 samples at a time into a 96-deep-well plate. An aliquot (185 μL) of each sample was dispensed into a single well, starting in column 1 and continuing for the remaining columns of the 96-deep-well plate. Pools were generated by repeating this process four additional times, until five samples were added to each well. The individual residual specimens remained separate and were stored refrigerated in case retesting or pool deconvolution was needed. On each 96-deep-well plate, 3 wells in column 12 were left empty to be used for negative (F12 and G12) and positive (H12) controls. Pooling 465 samples using the Biomek i5 and the script programmed to run the instrument took approximately 45 min.Alternatively, if individual samples were transferred without pooling, up to 93 samples  were transferred into a 96-deep-well plate containing Proteinase K. The direct transfer of 93 individual samples with the Biomek i5 took approximately 15 min.After the sample transfer was complete, sample plates were sealed with an adhesive film. Sealed plates were enclosed in a secondary container with a latched lid, along with the additional accession labels, and then the container was wiped with a disinfectant towel. The sample plate was then moved into the nucleic acid extraction room.As the Biomek transferred samples into pools in the 96-deep-well plates, the DART software tracked which samples were pooled and recorded the position of each sample and pool in the plate. When the sample transfer was complete, two reports were automatically generated as part of the Biomek method. One file contained the barcode identity of the original specimen, the rack, and the rack position it was in. The second file contained the listing of the barcodes in each pool. The Biomek method launcher automatically saved these files to a secured network file server. Rhapsody monitored this network directory and automatically processed the files and updated the accession record in the LIMS database. The sample identification field in the LIMS was updated with the barcode ID from the specimen tube, and the pool number was saved as part of the sample record. The rack and position information were combined and saved as the storage location for the sample. The order and position of each specimen tube were maintained when they were transferred from the Biomek racks to storage racks identified with the respective accession labels. Each Biomek rack has 16 tube positions and storage racks were arrayed in 6 columns of 16 tubes so that the sample order and positions mirrored the order in which they were scanned and pooled. This allowed us to use the rack and position values to uniquely locate any sample for pool deconvolution or the retesting of individual samples.As new accessions were created, they appeared in the working accessions tab of the application hub to provide real-time workflow tracking. Accession details and status were also displayed.The location of each sample in the 96-deep-well plate was maintained throughout the workflow so that pools could be traced back to the sample pool plate for confirmatory testing or deconvolution. From the PCR app, the appropriate accession number was entered, and the pool numbers or sample identities obtained from the barcode scanner populated a 96-well plate map without the need for manual data entry. Manual editing was optional so that individual samples or pools could be added to the plate. Once the map layout was complete, it was printed, and the hard copy accompanied the 96-deep-well plate throughout the laboratory workflow  was extracted from specimens using the Applied Biosystems MagMax™ Viral/Pathogen II Nucleic Acid Isolation Kit and the KingFisher Flex Magnetic Particle Processor  . ExtractNucleic acid extraction was performed in a dedicated extraction room that was isolated from the sample processing, RT-PCR mastermix preparation, and RT-PCR setup. Working in a biosafety cabinet with appropriate personal protective equipment, pools in the pooled sample plate were mixed 3 times by an Integra pipetting robot using filtered tips, and an aliquot of 200 μL was transferred into a 96-deep-well plate containing Proteinase K. For plates of individual sample tests, the Biomek i5 transferred samples directly into a deep-well plate containing Proteinase K. An aliquot of 200 μL VTM was added to the negative extraction control well (F12) on each plate. The prepared beads and binding solution were then added to the plate containing 200 μL sample and Proteinase K by the Integra pipetting robot. An accession label was added to the elution plate before extraction to maintain sample identity in the RT-PCR setup room. Sample and reagent plates were then loaded on the KingFisher Flex magnetic particle processor for automated NA extraction. Extraction was performed following manufacturer-provided scripts for the MagMax Viral/Pathogen II extraction kit, and the process took about 22 min. After extraction, the elution plate was sealed and placed on ice and then transferred to the RT-PCR setup room. The lot number of the extraction reagents used, the KingFisher Flex instrument identification, and the technician’s initials were recorded on the printed plate map.The Tetracore EZ-SARS-CoV-2 RT-PCR assay  was the assay of choice for testing  and was RT-PCR mastermix was prepared as directed by the manufacturer in a dedicated clean room. If multiple plates were expected, larger batches of mastermix were prepared and aliquoted into RT-PCR plates with a dedicated Integra pipetting robot. Plates containing mastermix were covered, marked with the time of mastermix preparation to ensure use within 2 h, and placed in ice buckets in the RT-PCR setup room. The lot number of the EZ-SARS-CoV-2 reagents used, the date, the time, and the technician’s initials were recorded on the printed mastermix recipe sheet and on the PCR plate map.In the dedicated RT-PCR setup room, elution plates were placed on the Integra pipetting robot base unit with the 96-well magnet installed to minimize the potential transfer of any beads remaining in the elution. PCR plates filled with mastermix were also placed on the Integra base, in the same orientation as the elution plate. The Integra pipetting robot was used to transfer the NA elutions into the RT-PCR plate containing mastermix, and the combined contents were mixed by pipetting up and down three times . NotatioAmplification conditions and analyses were performed as directed by the EZ-SARS-CoV-2 assay manufacturer. All amplification curves were inspected during analysis. Additionally, negative and positive control wells were assessed for expected outcomes. If the results of the control wells were not as expected, the assay was repeated. Amplification of the inhibition control was expected to result in a narrow range of Ct values within a run. If the inhibition control was not detected, the sample was determined to be invalid. If the human RNase P gene amplification signal resulted in a Cy5 Ct value of 37.05 or greater, the sample was determined to be invalid. This Cy5 Ct value cutoff was established from the amplification of serial dilution replicates, which revealed that Cy5 Ct values greater than 37.05 exhibited diminished repeatability. A cutoff was calculated for the SARS-CoV-2 target based on the FAM Ct values at the EZ-SARS-CoV-2 assay’s limit of detection; if the FAM Ct value of an individual sample was greater than 37.09, the test was repeated. If the second result was discordant , the result was determined to be inconclusive. Analysis and quality control checks were recorded on the PCR plate map, along with descriptions of any samples requiring additional review or repeated testing.Once the analysis was completed, the results were exported from the sequence detection software to be reviewed using the upload results from the PCR app. Highlighting was used to distinguish the control results from the samples and to flag positive results or Ct values that exceeded cutoffs. Results that were ready to be finalized were uploaded to the LIMS. Results of “not detected” were automatically finalized and submitted via a secure file transfer protocol (SFTP) service in Amazon Web Services (AWS) to the CMC reporting system.If a SARS-CoV-2 FAM Ct value was detected for a pool, each constituent sample of that pool was tested individually . The PCRAt the conclusion of testing each day, laboratory management used the daily reporting app to generate a PDF document summarizing all results finalized on that day. The results were broken down by accession, submission source, and results. Daily reports also included cumulative totals of tests, specimen types, and results. The daily report was automatically emailed to the laboratory management team and other designated individuals in the infection control group at the university.The equipment and instrumentation used in the CCTL are listed in A new restricted equipment network was created to isolate CCTL data and traffic. Access to this network was controlled through an access control list.https://aws.amazon.com/) cloud platform was used to create and manage the server and application infrastructure.The Amazon Web Services  database underlying the VetView  LIMS used by the Cornell Animal Health Diagnostic Center was duplicated to create a separate and dedicated instance of the LIMS for CCTL. The Oracle database ran in the AWS Relational Database Service, which met our requirements for high availability and durability.The Oracle SE2 version 12.1.0.2.v17 (https://www.python.org/) scripts were used to automate the Biomek method and workflow. Specifically, Python scripts were also written to direct the Biomek pooling strategy based on the number of specimens in the run and to track the specimens included in each pool. Additionally, scripts were written to track specimen identification and storage locations recorded through the Biomek barcode scanner.Python  was used to (1) monitor the database for new DART report outputs from the Biomek and use that to update the accession record in VetView, (2) upload the result files to the secure FTP service in the AWS cloud platform, and (3) distribute the daily report.https://angularjs.org/) framework for the front-end and Node.js (https://nodejs.org/en/) for the API back-end. The COVID-19 application hub was developed to provide a streamlined set of software apps to automate data entry and minimize manual input  message format from VetView LIMS and import them into Cayuga Medical Center’s electronic health record system, Meditech Expanse . The dashboards were monitored using Microsoft Power BI. An existing reporting interface was used to report the results to the Electronic Clinical Laboratory Reporting System (ECLRS), the New York state reportable disease database.https://www.sapstore.com/solutions/99043/SAP-Crystal-Reports?url_id=ctabutton-UnifiedSearchResult) was used to generate a daily report.SAP Crystal Reports software version 11.5.10  of these pools were comprised of 5 samples. Some pools  contained four or fewer individual samples. A total of 12,347 SARS-CoV-2-positive pools were deconvoluted, and another 489 pools were deconvoluted because of quality control checks. Of the SARS-CoV-2-positive pools, 9968 (80.7%) identified one positive individual sample per pool, and 1430 (11.6%) pools contained two positive individuals. During the fall of 2021, when the prevalence of positive samples was high, pools with more positive individual samples were detected: 118 pools contained three positive individuals, 6 pools contained four positive individuals, and 1 pool contained five positive individuals. The number of SARS-CoV-2-positive individuals identified from the university population during this time frame is shown in SARS-CoV-2-positive pools with Ct values less than 37.09 (LOD of the EZ-SARS-CoV-2 RT-PCR assay ) successThe SARS-CoV-2 Ct values of positive pools ranged from 9.73 to 44.12. The expected difference in Ct values between a positive pool and one constituent positive sample, spanning a five-fold dilution, is 2.32. The average difference observed between the SARS-CoV-2 Ct value of a positive pool and the Ct value of the deconvoluted individual positive sample was 2.18 with a standard deviation of 1.82, calculated from 9925 pools that contained one positive individual out of five samples . To mainThe turnaround time (TAT) from sample accessioning to result reporting to the CMC system was evaluated for the duration of the CCTL operation (17 August 2020 to 27 February 2023). The turnaround time was calculated separately for pooled samples tested for surveillance purposes, samples tested individually to deconvolute pools, and samples tested individually for contact tracing, adaptive testing, or cause. The median turnaround time for the results of the pooled samples was 4 h and 46 min , with a Overall, the majority of results were reported between 3 and 6 h for the pooled and individual samples, whereas deconvolution results were most often reported between 24 and 36 h . Prior tThe monitoring of assay performance was enabled by capturing all results in the Internal Control Tracking Dashboard of the COVID-19 application hub. Each month, a review was executed detailing the number of reactions performed and summarizing the performance of sample and control reactions. The numbers of samples reported as invalid, inconclusive, unsuitable, or not tested were listed, and a brief explanation for the results was included.The performance of the positive amplification control was plotted for the month to observe variability. Each positive amplification control Ct value observed above the expected pre-determined range was reviewed. Additionally, we evaluated whether an association existed between elevated positive amplification control Ct values and the ABI 7500 Fast real-time PCR instruments used during the month. The results from the negative extraction and negative amplification controls were reviewed for all runs every month, particularly confirming that no SARS-CoV-2 was detected in a negative control.The performance of the inhibition control was evaluated each month by plotting all control fluorophore Ct values. Minor fluctuations in Ct values are expected between the plates; in our experience, a Ct value of approximately 26 was most commonly observed. A representative plot of the control fluorophore Ct values for the month of March 2021  is provided in Seven quality indicator goals were set as measures of laboratory and testing performance. The goals were: (1) to maintain a specimen submission rejection rate of less than 1%; (2) to report 95% of results within 24–48 h of sample receipt; (3) to maintain a rate of less than 5% corrected reports; (4) to have zero non-conformances; (5) for complaint investigations to be 90% completed within 2 weeks; (6) for staff to achieve proficiency test performance of 100% for each testing event; and (7) for 100% of staff competency assessments to be completed on time. Each month, these indicators were assessed to determine whether the stated goals were met. If a goal was not met, a root cause analysis was performed to identify corrective actions. In most cases, all the quality indicators were met on a regular basis demonstrating the robustness of the workflow established in the CCTL.The robust high-throughput laboratory workflow described above enabled us to meet Cornell University surveillance testing needs during the COVID-19 pandemic . The laboratory tested a total of 2,079,685 samples between 17 August 2020 and 27 February 2023. This capacity and the rapid turnaround time were made possible by automating several steps of our workflow, including specimen accessioning, pooling, nucleic acid extraction, and PCR set-up. The CCTL’s capacity exceeded the university’s surveillance needs and thus the lab performed overflow testing of community specimens in partnership with CMC.The customized applications developed to support the workflow improved efficiency and minimized errors. We found it essential to involve application developers who understood the IT needs of a diagnostic laboratory and sample pooling workflow early in the process of establishing the laboratory. This enabled the rapid development of customized apps that enhanced the workflow. Continuous collaboration with the app developers allowed real-time improvements and updates in the apps as the workflow or the surveillance/testing programs changed. The specimen storage racking and tracking system devised specifically for the laboratory workflow was essential for efficiently accessing constituent specimens of positive pools for individual testing. The workflow also benefitted from the availability of the AWS cloud platform supporting the server and custom COVID-19 application infrastructure. Some IT solutions developed in CCTL are now being implemented in the Animal Health Diagnostic Center to support animal diagnostic testing and the performance of testing for the National Animal Health Laboratory Network (NAHLN).Testing pools of five samples was essential to our workflow and seemed to be of the appropriate size to maximize efficiency without losing sensitivity. Of the 370,839 pools tested, SARS-CoV-2 was detected in 12,347 pools, and 94.1% were confirmed to contain one or more positive individual samples. Most positive pools that did not identify a positive individual had a high SARS-CoV-2 Ct value, with 75.2% at or beyond the assay’s limit of detection (Ct > 37.09). Good agreement was observed for the difference in Ct values between a positive pool and the constituent positive individual samples, regardless of specimen type. Requiring testing of all members of the community, the rapid identification of positive individuals and placement in isolation combined with rigorous contact tracing efforts minimized the spread of SARS-CoV-2 on campus and through the surrounding community during fall 2020 and spring 2021 semesters, as shown in The turnaround time was monitored regularly throughout CCTL’s operations. Turnaround time calculations began at accession creation rather than the sample collection time because the lab’s operation schedule fluctuated to adapt to the surveillance program’s needs. At the beginning of semesters when many people returned to the Ithaca, NY, area and when the SARS-CoV-2 prevalence of positive samples was high, a same-day result turnaround was expected. However, workflow efficiency was hampered by the rate of sample collection and delivery when performing same-day testing. When the SARS-CoV-2 prevalence was low, the lab shifted to next-day testing so that all samples that would be tested were delivered the previous evening. When sample numbers were low, a hybrid system was employed in which samples from the previous day were tested as well as samples collected early on the same day. During fall 2021, the lab was closed on Saturdays, and, occasionally, samples delivered to the laboratory late on Friday night were pooled, but testing and reporting were not finalized until Sunday afternoon, resulting in maximum pool test turnaround times of 51 h and positive pool deconvolution turnaround times of 72 h.Staffing the laboratory through fluctuating testing volumes and SARS-CoV-2 prevalence was challenging. In the fall of 2020, the lab operated with fewer than 10 staff, largely drawing on existing Animal Health Diagnostic Center staff experienced in molecular diagnostic testing. In preparation for higher testing demands, six more full-time technicians were hired for the Spring 2021 semester. When the sample volume and the prevalence of positive samples were low over the summer of 2021, many staff returned to or were hired by the Animal Health Diagnostic Center. Most of those staff were recalled to CCTL for student arrival testing in late August. From August 2020 to December 2021, CCTL was operated in one and a half shifts 5 days a week (Mon–Fri) and half shifts on Saturdays and Sundays. The ability to flex the number of staff assigned to the CCTL was instrumental in our success.Within two years of the detection of the index SARS-CoV-2 case in Wuhan, China, in December 2019 ,17. Theshttps://tompkinscountyny.gov/health/COVID-19-omicron-variant, last accessed on 5 June 2023). The following day yielded the largest increase in cases on a single day since the onset of the pandemic in Tompkins County . In the following week, 2478 positive samples were reported by our laboratory; this represents 22.7% of all positive results determined by the laboratory up to that point. The Omicron variant spread rapidly through the Cornell University and Tompkins County population, reaching a peak incidence of 9.21% on a single day, despite the fact that more than 70% of this population was fully vaccinated. Omicron was initially described in South Africa and classified as a VOC on 26 November 2021 by the World Health Organization, shortly before its detection in Ithaca, NY [Detection of the Omicron (B.1.1.529) COVID-19 variant was first reported by Tompkins County on 11 December 2021 via the sequencing of positive cases performed at the Cornell University Virology Lab, , swine influenza virus (IAV-S), Ebola virus (EBOV), Nipah virus (NiPV), porcine epidemic diarrhea virus (PEDV), and African swine fever virus (ASFV), which could result in large epidemics or pandemics in which high-throughput testing will be needed ,28,29,30


Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of  Proteins are molecular machines that perform a diverse set of cellular processes, frequently forming complexes via protein–protein interactions (PPIs). As a result, PPIs have emerged as important targets for drug development, with peptide therapeutics designed to disrupt these interactions garnering attention due to their high specificity and low immunogenicity ,2,3. MosChemical inhibitors  have been historically preferred for therapeutics due to their ease of synthesis and cell membrane permeability . HoweverGenerating highly specific peptide therapeutics based on protein structure is computationally intense . Computain-silico using advanced algorithms and AI offer new possibilities for generating peptide therapeutics with high specificity . This variant retains metabolic activity while preventing mitogenic interactions with FGFR. Using this peptide-linked FGF1 variant, the authors found that the AlphaFold2-generated peptide was critical to associate FGF1 to skeletal muscle [in-vivo and in-vitro assays including fluorescence microscopy, protein-based assays, and in-vivo mouse monitoring assays. Before this study, long-term application of the naïve FGF1ΔHBS to mice resulted in several major disadvantages including weight loss, loss of appetite, and death. With the new AlphaFold2 linked peptide—FGF1ΔHBS conjugate, these side effects were reported to be reduced [A recent study used AlphaFold2 to generate a peptide that targets a biomarker of diabetes . In thisl muscle . This no reduced .Another recent example of using AlphaFold2 to develop peptide therapeutics is the development of the N1S peptide . In thisAlphaDesign is a similar method that predicts the 3D structure of a peptide from its amino acid sequence, using a generative adversarial network architecture that is trained on a dataset of protein structures and incorporates AlphaFold within an optimized design process . AlphaFoIn recent years, several deep learning-based methods have been developed for predicting the functions and structures of proteins. DeeProtein is one such method that utilizes residual and fully convolutional neural network architecture for the multi-label classification of protein sequences into 539 functional classes . ProDCoNDeepCNF is an extension of Conditional Neural Fields (CNF) that integrates conditional random fields and shallow neural networks, allowing it to model complex sequence-structure relationships and interdependencies between adjacent secondary structure labels . ExperimRoseTTAFold is a highly accurate method for predicting protein structures that uses three tracks representing the amino acid sequence, inter-residue distances, and 3D coordinates of the protein . By traiab-initio against the SARS-CoV-2 spike protein. Specifically, the authors report that thousands of potential peptides were predicted using Rosetta. From an initial pool of 2.5 thousand peptides, a combination of microarray screening and ELISAs reduced this pool to 4 peptide candidates [Rosetta was previously used to generate small peptide inhibitors against the SARS-CoV-2 (the virus responsible for the COVID-19 pandemic) spike protein and to BRAF—a member of the RAF-kinase family ,56. At tndidates . These cndidates . This st50 of 364 nM to WT BRAF and 172 nM against oncogenic BRAF [in-vitro experimental validation [In another study, Rosetta was used to design several peptides against the sequence that is thought to mediate the BRAF PPI . Using tnic BRAF . Additiolidation .The computational methods discussed thus far can predict the complex and diverse structures of peptides, such as α-helices, β-sheets, and disulfide-rich peptides with high accuracy. The development of these methods has been driven by the need to understand the structure and function of peptides, which play important roles in biological systems . These mProtein mimicry refers to the process of manipulating and designing peptides to mimic the structural and functional characteristics of small molecules. Peptides designed in this manner can therefore play crucial roles in various physiological processes, and their manipulation has the potential to serve as a key strategy for the development of novel drugs and therapies for various diseases ,57. Compin-vivo [The DeNovo mimic approach is a promising strategy for designing novel molecules with potential biomedical applications. One such application is the development of bone morphogenetic protein (BMP) mimics, which are peptides that can induce bone and cartilage formation . Researcin-vivo . This apin-vivo . The desin-vivo .The DeNovo mimic approach has also been used to design a modified CRISPR-Cas9 system, dCas9, which targets the Polycomb Repressive Complex 2 (PRC2) inhibitor to specific DNA sequences to facilitate gene expression . dCas9 wStructural-guided design is an approach that combines topological data analysis and machine learning to design stable and functional protein variants . One notMycobacterium tuberculosis [Recent use of this technology has yielded several peptides that can interfere with consequential drug targets. A notable example is recent work performed by Kaur and colleagues, who used this technology to develop peptides that target the RNA polymerase of the human pathogen rculosis . Specifirculosis . Of the in-vivo applications, the authors found that these peptides displayed a 100% efficiency in reducing viral infection at a concentration of 1 µM, highlighting the affinity of these designed peptides [During the COVID-19 pandemic, there was a necessity to rapidly develop a wide range of therapeutics to prevent infection. Early in the pandemic, the ACE2 receptor became not only the target, but also the template for the design of many of these therapeutics, as ACE2 is responsible for the entry of the SARS-CoV-2 virion into the host cells. To this point, a recent study performed by Karoyan and colleagues used protein mimicry to develop peptides that block SARS-CoV-2 entry into pulmonary cells . In thispeptides .In addition to human pathogens, structural-guided peptide design can also be applied to mammalian proteins. One such example is a recent study performed by Cardote and Ciulli, which used this technology to design peptides against the interaction between E3-ligases and adaptor proteins . The purAnother recent study assessed whether structural-guided peptide design can improve the T-cell receptor (TCR) specificity . TCRs rein-vitro studies [Another area of research involves the binding interactions of small molecules with RNA G-quadruplexes, which play important roles in gene regulation and cellular processes. By identifying structural features of small molecules that selectively stabilize RNA G-quadruplexes, researchers have the potential to develop new drugs that target these specific structures . Lastly, studies . RITA, a studies .The modularity of SMs offers a broad range of potential drug targets, thereby allowing for the generation of multifunctional peptides with different specificities. Due to being highly conserved across species, SMs are useful for the development of peptide therapeutics with reduced efficacy gaps in animal models ,20. AddiPIPE leverages SMs found in query proteins that mediate other known interactions to generate its predictions . SpecifiDe Novo is a comparable PPI prediction algorithm that leverages SMs in primary sequences to evaluate host-virus interactions . Unlike Another tool that can be used to predict protein-peptide interactions is GalaxyPepDock . This toPIPE was expanded upon in 2011 with the development of PIPE-Sites, which aimed to analyze the topology of the result matrix output by PIPE to automate PPI analysis, enabling the exploration of SM discovery at the scale of entire proteomes . PIPE-SiCurrently, several additional databases and tools are specific to SM annotation and discovery. DIscovery of LInear MOTifs (DILIMOT) is an SM discovery tool that utilizes protein FASTA sequences as input in addition to using BLAST to find orthologous groups and MUSCLE for multiple sequence alignments within intrinsically disordered regions. These are then analyzed by a pattern-matching algorithm to find motifs . The ShoIn 2014, PIPE was expanded to increase its efficacy by parallelizing it, resulting in Massively Parallel-PIPE (MP-PIPE) . MP-PIPEHeterodera glycines is an agricultural pathogen that affects soybean, the latter having three billion putative PPIs [H. glycines using cross-species proxies Arabidopsis thaliana and Caenorhabditis elegans [H. glycines. A post-experimental validation called Reciprocal Perspective for Improved Protein–Protein Interaction Prediction was conducted to decrease the false-positive rate in PIPE4 [The latest version of PIPE, namely PIPE4, utilizes interaction graphs to solve the interactomes of poorly annotated organisms . PIPE’s ive PPIs . We used elegans . This apin PIPE4 . This vain PIPE4 . We founin PIPE4 .In-Silico Protein Synthesizer (InSiPS) is a novel method for designing inhibitory peptides capable of selectively binding and inhibiting specific target proteins in living organisms [The rganisms . The proAn important attribute of InSiPS is the negative selection of the peptides . For eacin-vivo: Rmd1 (cytosolic sporulation protein), Pin4 (DNA damage repair protein), and Psk1 (serine/threonine protein kinase). The anti-Pin4 and anti-Rmd1 peptides displayed inhibitory activity similar to the phenotypes associated with PIN4 and RMD1 deletions, respectively. Specifically, we found that WT yeasts treated with the anti-Pin4 peptide displayed a sensitivity phenotype to 0.1 M of arsenite in a manner similar to WT untreated yeasts. These results were further supported by a yeast-2-hybrid assay which demonstrated the ability of both anti-Pin4 and anti-Psk4 peptides to bind to Pin4 and Psk1. We also directly evaluated the binding affinity for these peptides using an in-vitro walking array. We found that anti-Psk1 displayed a Kd of 2.2 nM, indicating a strong interaction between the peptide and the target protein. In these experiments, anti-Rmd1 failed to demonstrate increased sensitivity to β-mercaptoethanol or L-1,4-dithiothreitol, as would be seen in an rmd1Δ strain.To this point, a proof-of-concept experiment demonstrated that InSiPS can design peptides that inhibit the function of yeast proteins . The pepRecently, InSiPS was utilized to design peptides against SARS-CoV-2 surface protein S . To accoin-vitro assay as well as in an in-vivo biosensor experiment (unpublished results). One of these peptides reduced the replication of the SARS-CoV-2 virus by more than 75% in cell culture analysis.In a manuscript under preparation, additional peptides designed in this way were evaluated for their therapeutic abilities to interfere with the SARS-CoV-2 life cycle. Of the 10 peptides evaluated, four appear to interfere with the binding of the viral S protein to its human host ACE2 cell receptor in an Although InSiPS uses primary sequences as inputs , the length of the peptide is an important factor to consider during design . Larger in-silico approaches to designing and generating peptide therapeutics each with benefits and drawbacks, two relevant questions emerge pertaining to the in-vivo application of synthetic peptides. Do synthetic peptides generated designed in-silico display bioactivity and can synthetic peptide toxicity be predicted?Synthetic peptides have a significant advantage over small-molecule drugs in that they are structurally complex which can enable a single peptide drug to interact with many of the target binding sites required for activation or deactivation. One example of a highly successful peptide drug is insulin . Variousin-silico tools have been developed that can predict the biological activity of synthetic peptides [Several peptides ,89,90,91peptides . PAAP bupeptides  and utilin-silico model for predicting the hemolytic activity of synthetic peptides.Another peptide prediction tool is HemoPred. With the rapid and widespread development of synthetic peptide therapeutics, understanding whether synthetic peptides can induce hemolysis is essential. HemoPred was developed for this purpose . This alin-vitro, the high accuracy of this in-silico model holds promise in the prediction of the anticancer activity of synthetic peptides [in-silico-based screening approach relies on the rank-ordered presence of anchoring amino acids as well as amino acids that are likely to mediate an interaction [In terms of deep learning algorithms, a recent tool that uses deep learning to predict the anticancer activity of peptides (DeepACP) was developed . Specifipeptides . These tpeptides ,93. In apeptides ,95,96. Tpeptides ,95. One eraction ,99,100.Though tools are available to predict peptide toxicity through inappropriate interactions, peptides can still bind to other targets if not developed with an anti-selection ,94,95,96in-vivo applications is in its infancy [in-vivo and in-vitro applications of designed peptides, many barriers still exist that prevent their widespread adoption, the most critical being approval by the Food and Drug Administration (FDA). To our knowledge, there is no FDA-approved peptide drug that was originally designed through computational approaches. It is noteworthy to briefly discuss the current barriers of such synthetic peptides that impact their FDA approval and thus large-scale adoption as therapeutics.Generating computationally designed peptides for  infancy ,103. The infancy . Despite infancy . Though Predicting and modeling peptide structures is a complicated task, as peptides can fold into complex three-dimensional structures . This caAnother barrier is the biological stability of synthetic peptides. Like every biomaterial, peptides are subject to enzymatic degradation . WhatsmoA final barrier to large-scale adoption of computationally designed peptides is manufacturing and cost-effectiveness ,111,112.We have discussed several methods and tools to develop and predict the activity of synthetic peptides. How then can these peptides be applied? Several examples have been discussed, such as anticancer and antiviral peptides ,84,91. AAlthough the initial version of InSiPS was computationally intensive, the recently modified version of the algorithm has a 100-fold improved speed. Using the latest version of InSiPS, we plan to initiate a very ambitious project—developing two peptides for every essential human protein. Our goal is to expand this approach to the entire proteome of humans and eventually other organisms . With every peptide successfully designed by InSiPS, the algorithm undergoes further training, thereby becoming faster. This is an important feature, as the demonstrates the power and process of AI-designed therapeutics as becoming increasingly efficient. Thus, it is likely that AI will become an integral technology in the development of disease therapeutics. Instead of solely relying on traditional therapeutic development, the use of AI in therapeutic design has the potential to dramatically increase the speed and efficiency of peptide therapeutics.