Selection Of Endpoints Research Articles

Disease progression models of familial frontotemporal lobar degeneration and the temporal ordering of biomarker changes in an international cohort

AbstractBackgroundClinical trials are underway to treat familial frontotemporal lobar degeneration (f‐FTLD). This is a rare disease, and a limited number of mutation carriers have been identified; thus, efficient trial design is critical. Multimodal, latent disease progression models (DPM) can estimate time to symptom onset and define the temporal ordering of biomarker changes. DPMs can also be leveraged to select endpoints and potentially supplement analyses by integrating historical data. Recent draft FDA guidance for gene therapy trials in neurological disease supports these novel approaches to clinical trials.MethodParticipants included 1,049 members of families affected by f‐FTLD, due to mutations in GRN, MAPT, or C9orf72 genes, who were enrolled in ALLFTD or GENFI. A Bayesian repeated measures model incorporated multimodal data to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 677 mutations carriers (GRN (n=233), MAPT (n=151) and C9orf72 (n=293)). Family members without pathogenic mutations were used as the reference group. Mean follow‐up was 1.1 (SD=1.1) years. Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD Box Score, MRI volumes of brain regions affected by f‐FTLD, and plasma levels of neurofilament light chain (NfL).ResultDisease progression curves were similar across ALLFTD and GENFI cohorts. Plasma NfL elevations occurred earliest, up to 10 years before symptom onset, and NfL was the most powerful endpoint in the asymptomatic stage. MRI abnormalities occurred next, closer to symptom onset. The earliest MRI changes relative to symptom onset were observed in C9orf72+. GRN mutation carriers showed the most rapid acceleration in all biomarkers, and this acceleration occurred in close proximity to symptom onset. Neuropsychological measures and CDR®+NACC‐FTLD Box Score were among the most promising endpoints in the symptomatic stage. Trial simulations indicated that using latent disease age as an enrollment criterion would allow some asymptomatic mutation carriers to be enrolled without sacrificing power.ConclusionSimilarity in disease progression across ALLFTD and GENFI participants suggests these models will apply to international trials. Model‐derived estimates of disease progression curves indicate that endpoint selection should be specific to disease stage and mutation, and DPMs would facilitate greater participant enrollment.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Interest in real‐world data (RWD) and real‐world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third‐party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single‐arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness “big” RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient‐derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

Clinical Trials

Clinical trials (a.k.a. clinical studies) in vaccinology are investigations with humans to assess the immunogenicity, reactogenicity i.e., the expected local or systemic symptoms of the desired immune response, safety and/or efficacy or effectiveness of vaccines. Such investigations must be designed, conducted, and analysed based on scientific principles to get sound answers to specific questions stated in the trial plan. Since Clinical Trials involve human subjects, highest ethical standards need to be applied. In addition, national laws, licensing regulations and international standards, for example Declaration of Helsinki, regulate the procedures and conduct of clinical trials. Vaccine trials can be classified by development phase (phase I-III before licensure; phase IV post-licensure); by purpose; or role of the investigator. The study protocol covers design, selection of study subjects, selection of endpoints, methods to minimize bias, conduct of the study and analysis plan, all aimed at answering the study question with best possible internal scientific validity.

Human Genomics and Drug Development.

Insights into the genetic basis of human disease are helping to address some of the key challenges in new drug development including the very high rates of failure. Here we review the recent history of an emerging, genomics-assisted approach to pharmaceutical research and development, and its relationship to Mendelian randomization (MR), a well-established analytical approach to causal inference. We demonstrate how human genomic data linked to pharmaceutically relevant phenotypes can be used for (1) drug target identification (mapping relevant drug targets to diseases), (2) drug target validation (inferring the likely effects of drug target perturbation), (3) evaluation of the effectiveness and specificity of compound-target engagement (inferring the extent to which the effects of a compound are exclusive to the target and distinguishing between on-target and off-target compound effects), and (4) the selection of end points in clinical trials (the diseases or conditions to be evaluated as trial outcomes). We show how genomics can help identify indication expansion opportunities for licensed drugs and repurposing of compounds developed to clinical phase that proved safe but ineffective for the original intended indication. We outline statistical and biological considerations in using MR for drug target validation (drug target MR) and discuss the obstacles and challenges for scaled applications of these genomics-based approaches.

Anticipating EGFR Targeting in Early Stages of Lung Cancer: Leave No Stone Unturned.

Background: The current treatment landscape of early stage lung cancer is rapidly evolving, particularly in EGFR mutant non-small cell lung cancer (NSCLC), where target therapy is moving to early stages. In the current review, we collected the available data exploring the impact of EGFR targeting in both neoadjuvant and adjuvant settings, underlying lights and shadows and discussing the existing open issues. Methods: We performed a comprehensive search using PubMed and the proceedings of major international meetings to identify neoadjuvant/adjuvant trials with EGFR tyrosine kinase inhibitors (TKIs) in NSCLC. Results: Limited data are available so far about the activity/efficacy of neoadjuvant TKIs in EGFR mutant NSCLC, with only modest downstaging and pathological complete response rates reported. Differently, the ADAURA trial already proposed osimertinib as a potential new standard of care in resected NSCLC harboring an activating EGFR mutation. Conclusion: Anticipating targeted therapy to early stage EGFR mutant NSCLC presents great opportunities but also meaningful challenges in the current therapeutic/diagnostic pathway of lung cancer care. Appropriate endpoint(s) selection for clinical trials, disease progression management, patients’ and treatment selection, as well as need to address the feasibility of molecular profiling anticipation, represent crucial issues to face before innovation can move to early stages.

Selection of Endpoints for Clinical Studies of Ophthalmic Drugs

Until now, there have been no effective treatments for some ophthalmic diseases that have high social significance. Development of therapeutic approaches to such diseases may be complicated due to challenges in diagnosis and selection of clinical trial endpoints. The aim of the study was to analyse current approaches to selection of endpoints in clinical trials of ophthalmic drugs. Clinical efficacy studies of new medicinal products use surrogate endpoints in addition to clinical endpoints. However, currently used surrogate endpoints are not always relevant and do not fully reflect changes in the status of patients with chronic or progressive diseases. The study analysed published approaches to the selection of endpoints in clinical studies of ophthalmic drugs intended for the treatment of glaucoma, uveitis, dry eye syndrome, and age-related macular degeneration. It was demonstrated that the choice of surrogate endpoints in a clinical trial should take into account specific aspects of a particular disease. The assessment of dynamic patterns of changes in visual functions generally requires a complex approach for a comprehensive characterisation of the eye condition in a particular disease. The paper analyses the possibility of using potential surrogate endpoints in studies of the most common eye diseases, and highlights that none of them has been recommended for use in clinical trials or routine clinical practice.

Practical Needs in Assessing Response to Therapy in Operated Brain High Grade Glioma According to Response Assessment in Neuro-Oncology Criteria

Background: Tumors known as gliomas begin in the brain or spine's glial cells and might spread throughout the body. An effort was made to improve tumor response evaluation and end point selection through the Response Assessment in Neuro-Oncology (RANO) working group. Objective: To standardize the assessment method and results reporting by applying MRI-RANO criteria in detecting glioma response to surgical treatment. Patients and Methods: This was a prospective cohort study included 12 patients (4 males and 8 females) whose mean age was 53.6 ± 15.1years. Included patients are those who were operated and pathologically proved as brain glioma grade IV (GBM). They underwent post-operative MRI within 48 hours and are available for follow up MRI after 3 months. Imaging modalities applied in both MRI exams were conventional magnetic resonance imaging, MRI diffusion weighted images, and contrast imaging.RANO criteria were applied. Results: According to RANO criteria, none of the lesions had pseudo response or pseudo progression. However, two thirds (66.7%) had progressive disease and one third (33.3%) had complete response. There was statistically significant association between MRI findings 3 months postoperative and RANO criteria as patients with compete response had statistically significant decrease on measurable solid components, diffusion restriction, post contrast enhancement and all lesions had grade I edema with no mass effect or midline shift compared to patients with progressive disease. 4 cases that showed complete response category had fulfilled all the RANO criteria, while 8 cases with category progressive disease had fulfilled more than one of the described RANO criteria. Conclusion: RANO criteria are an effective tool to be used in interpretation of MRI for follow-up of surgically operated glioma patients to detect their response.

Refining neoadjuvant therapy clinical trial design for muscle-invasive bladder cancer before cystectomy: a joint US Food and Drug Administration and Bladder Cancer Advocacy Network workshop.

The success of the use of novel therapies in the treatment of advanced urothelial carcinoma has contributed to growing interest in evaluating these therapies at earlier stages of the disease. However, trials evaluating these therapies in the neoadjuvant setting must have clearly defined study elements and appropriately selected end points to ensure the applicability of the trial and enable interpretation of the study results. To advance the development of rational trial design, a public workshop jointly sponsored by the US Food and Drug Administration and the Bladder Cancer Advocacy Network convened in August 2019. Clinicians, clinical trialists, radiologists, biostatisticians, patients, advocates and other stakeholders discussed key elements and end points when designing trials of neoadjuvant therapy for muscle-invasive bladder cancer (MIBC), identifying opportunities to refine eligibility, design and end points for neoadjuvant trials in MIBC. Although pathological complete response (pCR) is already being used as a co-primary end point, both individual-level and trial-level surrogacy for time-to-event end points, such as event-free survival or overall survival, remain incompletely characterized in MIBC. Additionally, use of pCR is limited by heterogeneity in pathological evaluation and the fact that the magnitude of pCR improvement that might translate into a meaningful clinical benefit remains unclear. Given existing knowledge gaps, capture of highly granular patient-related, tumour-related and treatment-related characteristics in the current generation of neoadjuvant MIBC trials will be critical to informing the design of future trials.

Stroke recovery enhancing therapies: lessons from recent clinical trials.

Poststroke recovery processes include restoration or compensation of function, respectively functions initially lost or new functions acquired after an injury. Therapeutic interventions can enhance these processes and/or reduce processes impeding regeneration. Numerous experimental studies suggest great opportunities for such treatments, but the results from recent large clinical trials using neuromodulators such as dopamine and fluoxetine are disappointing. The reasons for this are manifold affecting forward translation of results from animals models into the human situation. This “translational road block” is defined by differences between animals and humans with regard to the genetic and epigenetic background, size and anatomy of the brain, cerebral vascular anatomy, immune system, as well as clinical function and behavior. Backward blockade includes the incompatible adaption of targets and outcomes in clinical trials with regard to prior preclinical findings. For example, the design of clinical recovery trials varies widely and was characterized by the selection of different clinical endpoints, the inclusion a broad spectrum of stroke subtypes and clinical syndromes as well as different time windows for treatment initiation after infarct onset. This review will discuss these aspects based on the results of the recent stroke recovery trials with the goal to contribute to the currently biggest unmet need in stroke research - the development of a recovery enhancing therapy that improves the functional outcome of a chronic stroke patient.

A critical appraisal of registry-based objective performance goals in peripheral arterial disease

The multidisciplinary Superficial Femoral Artery-Popliteal EvidencE Development (SPEED) Study Group, under the auspices of the Registry Assessment of Peripheral Interventional Devices (RAPID) partnership, recently published objective performance goals for peripheral vascular interventions in the femoropopliteal arteries. Retrospective outcomes from the Vascular Quality Initiative provided the sole study data source. Strengths and weaknesses of this landmark effort are examined. Critical concerns include the substantial risks of ascertainment bias, flawed end point selection, sparse and variable capture of midterm follow-up data, and lack of expected discrimination between treatment modalities. The current Vascular Quality Initiative registry data thus appear insufficiently robust for the generation of objective performance goals and practice benchmarks; suggestions for redesign are provided. The impact of the statutory framework of the US Food and Drug Administration on device approval pathways and the maturation of an evidence-based approach to peripheral vascular intervention is explored.

International consensus recommendations on key outcome measures for organ preservation after (chemo)radiotherapy in patients with rectal cancer.

Multimodal treatment strategies for patients with rectal cancer are increasingly including the possibility of organ preservation, through nonoperative management or local excision. Organ preservation strategies can enable patients with a complete response or near-complete clinical responses after radiotherapy with or without concomitant chemotherapy to safely avoid the morbidities associated with radical surgery, and thus to maintain anorectal function and quality of life. However, standardization of the key outcome measures of organ preservation strategies is currently lacking; this includes a lack of consensus of the optimal definitions and selection of primary end points according to the trial phase and design; the optimal time points for response assessment; response-based decision-making; follow-up schedules; use of specific anorectal function tests; and quality of life and patient-reported outcomes. Thus, a consensus statement on outcome measures is necessary to ensure consistency and facilitate more accurate comparisons of data from ongoing and future trials. Here, we have convened an international group of experts with extensive experience in the management of patients with rectal cancer, including organ preservation approaches, and used a Delphi process to establish the first international consensus recommendations for key outcome measures of organ preservation, in an attempt to standardize the reporting of data from both trials and routine practice in this emerging area.

Collision‐free local planner for unknown subterranean navigation

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.

Early-Phase Interventional Trials in Oral Cancer Prevention.

Simple SummaryOral cancer is a devastating disease with increasing incidence worldwide. Oral epithelial dysplasia (OED) is a potentially malignant disorder and patients with OED are at increased risk of developing oral cancer. Current strategies for management of OED include surgery or close observation and both fail to address the underlying pathogenesis of the disease. There is an urgent need for evidence-based medical treatments for OED to prevent oral cancer development in this cohort. Chemoprevention trials to date have not delivered therapeutic agents for routine clinical practice. Historically, there has been significant heterogeneity in the design of oral cancer chemoprevention trials, with most failing to selectively recruit patients with biopsy-proven OED, which limits the usefulness of the findings in the OED population. The present paper aims to review the current evidence and the methodology of early-phase trials in oral cancer chemoprevention. Novel strategies in oral cancer chemoprevention will also be discussed.The increasing breadth of molecular targets, promise of immune-targeted therapies and repurposed agents have heightened interest in cancer prevention. While, to date, testing of oral cancer chemoprevention strategies has failed to deliver therapeutic agents for routine clinical practice, there remains an urgent need for further clinical research to overcome this hurdle. Patients at the greatest risk of disease stand to benefit the most from inclusion in clinical trials; therefore, there is a need to carefully define this population using validated clinical and molecular markers. Safety, tolerability and the efficacy of interventions is assessed through carefully selected endpoints. These endpoints may include pharmacodynamic, clinical, histological and on-target molecular modifications as an individual or as a composite endpoint. Early-phase trials provide an area of opportunity to explore novel and repurposed agents in the setting of oral cancer chemoprevention, eventually leading to phase III trials with clinical endpoints such as transformation and clinical outcome; these studies are large, lengthy and expensive and should be reserved for the most promising of agents. This paper will explore current evidence in oral cancer chemoprevention, drug repurposing, selection of appropriate endpoints for early-phase trials and novel therapeutic angles in oral cancer chemoprevention.

SY16-5 Problems in clinical trials to evaluate de-escalation

Recently, de-escalation of treatment has been evaluated in some clinical trials for breast cancer. If intensive treatments do not improve survival more than less intensive treatments, less intensive treatments may be better in terms of quality of life, toxicity, cost, and some burdens. To design a clinical trial of de-escalation of treatment, many factors should be considered such as definition of treatment (regimen), population selection (evaluation of biomarker), selection of endpoints (use of multiple endpoints), randomization, and analysis methods. For example, when de-escalation is evaluated in the non-inferiority setting, it may be difficult to conduct a randomized controlled trial because of a large sample size, and how to use multiple endpoints, such as overall survival, toxicity, quality of life, and cost, may also be difficult. In this talk, I discuss the use of historical data and multiple endpoints in clinical trials of de-escalation of treatment.

Abstract 894: Self-serve data and cohort selection in the California Teachers Study: A web-based tool

Abstract Background: Cancer Epidemiology Cohorts (CECs) amass vast amounts of participant health, lifestyle, environmental, genetic, and biologic data. Sharing these well-annotated participant data supports research across diverse cancer outcomes. CEC data often contain PHI, which limits use of open-access databases that have become a boon to other fields. Instead, most CECs create custom datasets for each project, which is labor intensive and hinders data sharing. Objective: The California Teachers Study (CTS), a prospective CEC of 133,477 women that began in 1995, sought to address this issue by building a user-friendly tool for researchers to independently and flexibly choose CTS data—i.e., to execute cohort selection—in a web-based platform. We also aimed to maintain existing data privacy and security; support a full range of study designs, exposures, and outcomes; and provide real-time query result visualizations. Methods: To support these computational demands, we chose an open-source column-oriented database management system optimized for fast analysis of large volumes of data. We curated and tagged participant self-reported data for improved searching and sorting. We built conditional queries that are modified by user selections, and included free text entry to handle outliers. To address privacy, the web-based tool displays summary data in aggregate and outputs the final dataset to a secure server. Users select their cancer endpoint definitions by SEER code, site group name, or ICD code; select analysis start and end points by participant-specific event type or hard-coded date; opt in or out of various censoring rules; and select self-reported data by questionnaire, topic, or search terms. After users submit the query, a folder is created for their project in the secure CTS remote desktop environment, which contains the dataset, a custom data dictionary, and starter scripts in SAS and in R. Results: Our first fully self-service data query module supports cancer cohort analyses and requires no CTS staff intervention to provision data. Two-thirds of recent CTS data requests have been cancer cohort analyses; if this continues, CTS could experience up to a 60% reduction in staff effort spent on creating data sets. This improvement enables instant access for researchers and improves data sharing for not only cancer cohort analyses, but across the full range of research projects. Discussion: A challenge to automating complex processes like cohort selection is focusing on edge cases. By focusing on automating the single most common request type (cancer cohort analyses), we immediately added value for our staff and users. The inclusion of data request modules for currently non-automatable study designs and data domains enables the tool to function as a single channel through which all data requests flow. Other CECs may also consider automating the most common aspects of their data request processes and sharing their results. Citation Format: Jennifer L. Benbow, Emma Spielfogel, Kai Lin, Sandeep Chandra, Paul Hughes, James V. Lacey. Self-serve data and cohort selection in the California Teachers Study: A web-based tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 894.

A randomized trial of exercise and diet on health-related quality of life in survivors of breast cancer with overweight or obesity.

Obesity is a chronic, relapsing, and progressive disease; it is associated with poor health-related quality of life (HRQOL) in survivors of breast cancer. In this 2 × 2 factorial trial, 351 survivors of breast cancer with overweight or obesity were randomized to 1 of 4 treatment groups for 52 weeks: control, exercise alone, diet alone, or exercise plus diet. HRQOL end points were measured at baseline and at week 52 using the 36-Item Medical Outcomes Survey-Short Form (SF-36). Repeated measures analysis of covariance quantified the estimated treatment difference (ETD). At baseline, participants had a mean (SD) age of 59.4 years (8.7), body mass index of 34.0 kg/m2 (5.9), and 71 participants (20.2%) self-reported fair or poor general health. After 52 weeks, compared with control, the exercise plus diet improved the physical health summary score (ETD: 5.39; 95% CI, 0.55-10.22); exercise alone (ETD: -1.91; 95% CI, -6.60 to 2.79) and diet alone (ETD: 3.16; 95% CI, -1.52 to 7.83) did not change the physical health summary score. Compared with control, exercise alone (ETD: -0.27; 95% CI, -6.60 to 2.79), diet alone (ETD: 3.25; 95% CI, -1.41 to 7.91), and the exercise plus diet (ETD: 1.75; 95% CI, -2.90 to 6.39) did not change the mental health summary score. Exercise alone did not impact any HRQOL subscale; diet alone improved the vitality subscale; exercise plus diet improved the physical functioning, role-physical and vitality subscales. In survivors of breast cancer with overweight or obesity, exercise plus diet improved select HRQOL end points at week 52.

Research and development of new drugs for nonalcoholic steatohepatitis: An unmet need in clinical practice

With the effective control of viral hepatitis around the world, nonalcoholic steatohepatitis (NASH) will become the main cause of liver transplantation in the next ten years. There is a huge number of NASH patients, but currently no drug has been approved by authorities, which represents a large unmet need in clinical practice. The complex pathogenesis of NASH, heterogeneity of this disease, difficulties in diagnosis, and selection of treatment endpoints have brought great challenges to the research and development of new drugs.

Signposts for Aquatic Toxicity Evaluation in China: Text Mining using Event-Driven Taxonomy within and among Regions.

Selection of toxicity endpoints affects outcomes of risk assessment. Scientific decisions based on more holistic evidence is preferable for designing bioassay batteries rather than subjective selections, particularly when systems are poorly understood. Here, we propose a novel event-driven taxonomy (EDT)-based text mining tool to prioritize stressors likely to elicit water quality deterioration. The tool integrated automated literature collection, natural language processing using adverse outcome pathway-based toxicological terminologies and machine learning to classify event drivers (EDs). From aquatic toxicity assessments within China over the past decade, we gathered over 14 000 sources of information. With a dictionary that included 1039 toxicological terms, 15 bioassay-related modes of actions were mapped, yet less than half of the bioassays could be elucidated by available adverse outcome pathways. To fill these mechanistic knowledge gaps, we developed a Naïve Bayesian ED-classifier to annotate apical responses. The classifier's 4-fold cross-validation reached 74% accuracy and labeled 85% bioassays as 26 EDs. Narcosis, estrogen receptor-, and aryl hydrogen receptor-mediators were the major EDs in aquatic systems across China, whereas individual regions had distinct ED fingerprints. The EDT-based tool provides a promising diagnostic strategy to inform region-specific bioassay design and selection for water quality assessments in a big data era.

Endpoints selection in registration clinical trials and the needs of real-world clinical practice with the example of anti-VEGF therapy in neovascular age-related macular degeneration

The issues of endpoints selection for regulatory requirements and real-world clinical practice using the example of anti-VEGF therapy in neovascular age-related macular degeneration (nAMD) are discussed in the article. New technologies (optical coherent tomography) introduction are shown to change clinical practice but not regulatory requirements on the endpoints. In the same time for regulatory purpose clinical trials design is changed from superiority to non-inferiority. The changes in the approach to primary endpoint selection are not anticipated due to regulators conservatism but there is a requirement to the comparison with best treatment alternative (i.e. same class comparator in case of anti-VEGF therapy) due to ethical reasons. To satisfy real-world clinicians need, the secondary endpoints are analyzed, but multiple testing problem appears. Statistical methods developed in recent years allow using specified comparison to be made without inflating Type I error. HAWK and HARRIER clinical trials demonstrated an example how superiority of brolucizumab over aflibercet on anatomical endpoints was reliably found.

Translational Medicine and Exercise Prescription (TMEP): Advancing the Era of Exercise Medicine

Translational Medicine and Exercise Prescription (TMEP): Advancing the Era of Exercise Medicine