Favorable Antiviral Effect of Metformin on Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load in a Randomized, Placebo-Controlled Clinical Trial of Coronavirus Disease 2019.

BACKGROUND: Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%. METHODS: COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction. RESULTS: The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95% confidence interval [CI], -1.05 to -.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo. CONCLUSIONS: In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology. CLINICAL TRIALS REGISTRATION: NCT04510194.

Efficacy and safety of liraglutide in patients with patients with an ileal pouch-anal anastomosis and chronic high bowel frequency: A placebo-controlled, crossover, proof of concept study.

Introduction: After colectomy with ileo-anal pouch anastomosis (IPAA), many patients develop high bowel frequency (BF) refractory to antimotility agents despite normal IPAA morphology. Low circulating levels of glucagon-like protein-1 (GLP-1), a modulator of gastroduodenal motility, have been reported after colectomy. Methods: Double-blind crossover study of 8 IPAA patients with refractory high BF treated with daily administration of the GLP-1 receptor agonist (GLP-1-RA) liraglutide or placebo. Results: Liraglutide, but not placebo, reduced daily BF by more than 35% (P<0.03). Discussion: Larger randomized controlled studies are warranted to delineate the treatment potential of GLP-1RA's in IPAA patients suffering from non-inflammatory high BF.

Association of Premorbid GLP-1RA and SGLT-2i Prescription Alone and in Combination with COVID-19 Severity.

INTRODUCTION: People with type 2 diabetes are at heightened risk for severe outcomes related to COVID-19 infection, including hospitalization, intensive care unit admission, and mortality. This study was designed to examine the impact of premorbid use of glucagon-like peptide-1 receptor agonist (GLP-1RA) monotherapy, sodium-glucose cotransporter-2 inhibitor (SGLT-2i) monotherapy, and concomitant GLP1-RA/SGLT-2i therapy on the severity of outcomes in individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: Utilizing observational data from the National COVID Cohort Collaborative through September 2022, we compared outcomes in 78,806 individuals with a prescription of GLP-1RA and SGLT-2i versus a prescription of dipeptidyl peptidase 4 inhibitors (DPP-4i) within 24 months of a positive SARS-CoV-2 PCR test. We also compared concomitant GLP-1RA/SGLT-2i therapy to GLP-1RA and SGLT-2i monotherapy. The primary outcome was 60-day mortality, measured from the positive test date. Secondary outcomes included emergency room (ER) visits, hospitalization, and mechanical ventilation within 14 days. Using a super learner approach and accounting for baseline characteristics, associations were quantified with odds ratios (OR) estimated with targeted maximum likelihood estimation (TMLE). RESULTS: Use of GLP-1RA (OR 0.64, 95% confidence interval [CI] 0.56-0.72) and SGLT-2i (OR 0.62, 95% CI 0.57-0.68) were associated with lower odds of 60-day mortality compared to DPP-4i use. Additionally, the OR of ER visits and hospitalizations were similarly reduced with GLP1-RA and SGLT-2i use. Concomitant GLP-1RA/SGLT-2i use showed similar odds of 60-day mortality when compared to GLP-1RA or SGLT-2i use alone (OR 0.92, 95% CI 0.81-1.05 and OR 0.88, 95% CI 0.76-1.01, respectively). However, lower OR of all secondary outcomes were associated with concomitant GLP-1RA/SGLT-2i use when compared to SGLT-2i use alone. CONCLUSION: Among adults who tested positive for SARS-CoV-2, premorbid use of either GLP-1RA or SGLT-2i is associated with lower odds of mortality compared to DPP-4i. Furthermore, concomitant use of GLP-1RA and SGLT-2i is linked to lower odds of other severe COVID-19 outcomes, including ER visits, hospitalizations, and mechanical ventilation, compared to SGLT-2i use alone. Graphical abstract available for this article.

Regional variation in cause of death in patients with type 2 diabetes: Insights from EXSCEL.

AIMS: Type 2 diabetes (T2D) is a risk factor for cardiovascular and non-cardiovascular mortality. However, global distribution of cause-specific deaths in T2D is poorly understood. We characterized cause-specific deaths by geographic region among individuals with T2D at risk for cardiovascular disease (CVD). METHODS AND RESULTS: The international EXSCEL trial included 14,752 participants with T2D (73% with established CVD). We identified the proportion of deaths over 5-year follow-up attributed to cardiovascular and non-cardiovascular causes, and associated risk factors. During median 3.2-year follow-up, 1,091 (7.4%) participants died. Adjudicated causes of death were 723 cardiovascular (66.3% of deaths), including 252 unknown, and 368 non-cardiovascular (33.7%). Most deaths occurred in North America (N = 356/9.6% across region) and Eastern Europe (N = 326/8.1%), with fewest in Asia/Pacific (N = 68/4.4%). The highest proportional cause-specific deaths by region were sudden cardiac in Asia/Pacific (23/34% of regional deaths) and North America (86/24%); unknown in Eastern Europe (90/28%) and Western Europe (39/21%); and non-malignant non-cardiovascular in Latin America (48/31%). Cox proportional hazards model for adjudicated causes of death showed prognostic risk factors (hazard ratio [95% CI]) for cardiovascular and non-cardiovascular deaths, respectively: heart failure 2.04 (1.72-2.42) and 1.86 (1.46-2.39); peripheral artery disease 1.83 (1.54-2.18) and 1.78 (1.40-2.26); and current smoking status 1.61 (1.29-2.01) and 1.77 (1.31-2.40). CONCLUSIONS: In a contemporary T2D trial population, with and without established CVD, leading causes of death varied by geographic region. Underlying mechanisms leading to variability in cause of death across geographic regions and its impact on clinical trial endpoints warrant future research.

Mortality in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: We report mortality outcomes in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) among people with type 2 diabetes diagnosed within 10 years and no recent history of cardiovascular events or cancer. RESEARCH DESIGN AND METHODS: Overall mortality rates and major causes of death were assessed over an average of 5 years of follow-up. Cause of death was adjudicated centrally by a committee masked to treatment assignment. We examined baseline covariates and the 10-year Framingham Risk Score for associations. RESULTS: Mortality rate was low (0.59 per 100 participant-years). Participants who died during follow-up were likely to be older, be male, have a history of hypertension, have a history of smoking, and have moderate albuminuria. The two most common underlying causes of death were "cardiovascular-cause" (a composite of underlying causes) (38.6%) and cancer (26.8%). There were no differences by treatment group. CONCLUSIONS: Among people with diabetes of relatively short duration, cause of death was varied. Attention to health risks beyond cardiovascular diseases is warranted.

Comparison of tirzepatide and dulaglutide on major adverse cardiovascular events in participants with type 2 diabetes and atherosclerotic cardiovascular disease: SURPASS-CVOT design and baseline characteristics.

BACKGROUND: Tirzepatide, a once-weekly GIP/GLP-1 receptor agonist, reduces blood glucose and body weight in people with type 2 diabetes. The cardiovascular (CV) safety and efficacy of tirzepatide have not been definitively assessed in a cardiovascular outcomes trial. METHODS: Tirzepatide is being studied in a randomized, double-blind, active-controlled CV outcomes trial. People with type 2 diabetes aged ≥40 years, with established atherosclerotic CV disease, HbA1c ≥7% to ≤10.5%, and body mass index ≥25 kg/m2 were randomized 1:1 to once weekly subcutaneous injection of either tirzepatide up to 15 mg or dulaglutide 1.5 mg. The primary outcome is time to first occurrence of any major adverse cardiovascular event (MACE), defined as CV death, myocardial infarction, or stroke. The trial is event-driven and planned to continue until ≥1,615 participants experience an adjudication-confirmed component of MACE. The primary analysis is noninferiority for time to first MACE of tirzepatide vs dulaglutide by demonstrating an upper confidence limit <1.05, which will also confirm superiority vs a putative placebo, and also to determine whether tirzepatide produces a greater CV benefit than dulaglutide (superiority analysis). RESULTS: Over 2 years, 13,299 people at 640 sites in 30 countries across all world regions were randomized. The mean age of randomized participants at baseline was 64.1 years, diabetes duration 14.7 years, HbA1c 8.4%, and BMI 32.6 kg/m2. Overall, 65.0% had coronary disease, of whom 47.3% reported prior myocardial infarction and 57.4% had prior coronary revascularization. 19.1% of participants had a prior stroke and 25.3% had peripheral artery disease. The trial is fully recruited and ongoing. CONCLUSION: SURPASS-CVOT will provide definitive evidence as to the CV safety and efficacy of tirzepatide as compared with dulaglutide, a GLP-1 receptor agonist with established CV benefit.

Geriatric Assessment Impairment Profiles and Mortality in Older Adults with Gastrointestinal Cancers: Latent Class Analysis of the CARE Registry.

BACKGROUND: Many older adults with cancer have ≥2 impairments on geriatric assessment which impacts present and future frailty status, treatment tolerability, and outcomes. Our objective was to identify and describe distinct geriatric assessment impairment classes using latent class analysis (LCA) in older patients with gastrointestinal malignancies and assess 1-year mortality. METHODS: We used the Cancer & Aging Resilience Evaluation (CARE) Study, a registry of older adults (≥60 years) at University of Alabama at Birmingham. The analytic cohort included patients with gastrointestinal malignancies who completed a self-administered geriatric assessment (CARE tool) before chemotherapy and had ≥1 geriatric assessment impairment. Thirteen geriatric assessment impairments were used as indicators in LCA. Resultant classes were described, mortality was estimated, and risk contrasts (differences, hazard ratios) were calculated with 95% confidence intervals. For comparison, estimates were provided for frailty categories (robust, pre-frail, frail) determined from 44 items in the CARE tool. Stratified analyses included high-risk (pancreatic, hepatobiliary, esophageal) vs. low-risk gastrointestinal cancers, and stage (IV vs. I-III). RESULTS: Six geriatric assessment impairment classes were identified: Mild impairment (LC1); Social support impairment (LC2); Weight loss alone (LC3); Impaired, low anxiety/depression (LC4); Impaired with anxiety/depression (LC5); Global impairment (LC6). One-year mortality was 14%, 22%, 29%, 34%, 50% and 50% for LC1-LC6, respectively. For frailty categories, estimates ranged from 18% (robust) to 40% (frail). In stratified analyses, LC4-LC6 consistently had higher mortality estimates compared to LC1. CONCLUSIONS: The 6 geriatric assessment impairment classes showed a wider spread of mortality estimates compared to frailty categories and could be used to identify vulnerable patients and to plan interventions.

Week-long normoglycaemia in diabetic mice and minipigs via a subcutaneous dose of a glucose-responsive insulin complex.

Glucose-responsive formulations of insulin can increase its therapeutic index and reduce the burden of its administration. However, it has been difficult to develop single-dosage formulations that can release insulin in both a sustained and glucose-responsive manner. Here we report the development of a subcutaneously injected glucose-responsive formulation that nearly does not trigger the formation of a fibrous capsule and that leads to week-long normoglycaemia and negligible hypoglycaemia in mice and minipigs with type 1 diabetes. The formulation consists of gluconic acid-modified recombinant human insulin binding tightly to poly-L-lysine modified by 4-carboxy-3-fluorophenylboronic acid via glucose-responsive phenylboronic acid-diol complexation and electrostatic attraction. When the insulin complex is exposed to high glucose concentrations, the phenylboronic acid moieties of the polymers bind rapidly to glucose, breaking the complexation and reducing the polymers' positive charge density, which promotes the release of insulin. The therapeutic performance of this long-acting single-dose formulation supports its further evaluation and clinical translational studies.

Case study of semaglutide and cardiovascular outcomes: An application of the Causal Roadmap to a hybrid design for augmenting an RCT control arm with real-world data.

Introduction: Increasing interest in real-world evidence has fueled the development of study designs incorporating real-world data (RWD). Using the Causal Roadmap, we specify three designs to evaluate the difference in risk of major adverse cardiovascular events (MACE) with oral semaglutide versus standard-of-care: (1) the actual sequence of non-inferiority and superiority randomized controlled trials (RCTs), (2) a single RCT, and (3) a hybrid randomized-external data study. Methods: The hybrid design considers integration of the PIONEER 6 RCT with RWD controls using the experiment-selector cross-validated targeted maximum likelihood estimator. We evaluate 95% confidence interval coverage, power, and average patient time during which participants would be precluded from receiving a glucagon-like peptide-1 receptor agonist (GLP1-RA) for each design using simulations. Finally, we estimate the effect of oral semaglutide on MACE for the hybrid PIONEER 6-RWD analysis. Results: In simulations, Designs 1 and 2 performed similarly. The tradeoff between decreased coverage and patient time without the possibility of a GLP1-RA for Designs 1 and 3 depended on the simulated bias. In real data analysis using Design 3, external controls were integrated in 84% of cross-validation folds, resulting in an estimated risk difference of -1.53%-points (95% CI -2.75%-points to -0.30%-points). Conclusions: The Causal Roadmap helps investigators to minimize potential bias in studies using RWD and to quantify tradeoffs between study designs. The simulation results help to interpret the level of evidence provided by the real data analysis in support of the superiority of oral semaglutide versus standard-of-care for cardiovascular risk reduction.

Iterative Causal Forest: A Novel Algorithm for Subgroup Identification.

Precisely and efficiently identifying subgroups with heterogeneous treatment effects (HTEs) in real-world evidence studies remains a challenge. Based on the causal forest (CF) method, we developed an iterative CF (iCF) algorithm to identify HTEs in subgroups defined by important variables. Our method iteratively grows different depths of the CF with important effect modifiers, performs plurality votes to obtain decision trees (subgroup decisions) for a family of CFs with different depths, then finds the cross-validated subgroup decision that best predicts the treatment effect as a final subgroup decision. We simulated 12 different scenarios and showed that the iCF outperformed other machine learning methods for interaction/subgroup identification in the majority of scenarios assessed. Using a 20% random sample of fee-for-service Medicare beneficiaries initiating sodium-glucose cotransporter-2 inhibitors (SGLT2i) or glucagon-like peptide-1 receptor agonists (GLP1RA), we implemented the iCF to identify subgroups with HTEs for hospitalized heart failure. Consistent with previous studies suggesting patients with heart failure benefit more from SGLT2i, iCF successfully identified such a subpopulation with HTEs and additive interactions. The iCF is a promising method for identifying subgroups with HTEs in real-world data where the potential for unmeasured confounding can be limited by study design.

Strategies used for the COVID-OUT decentralized trial of outpatient treatment of SARS-CoV-2.

The COVID-19 pandemic accelerated the development of decentralized clinical trials (DCT). DCT's are an important and pragmatic method for assessing health outcomes yet comprise only a minority of clinical trials, and few published methodologies exist. In this report, we detail the operational components of COVID-OUT, a decentralized, multicenter, quadruple-blinded, randomized trial that rapidly delivered study drugs nation-wide. The trial examined three medications (metformin, ivermectin, and fluvoxamine) as outpatient treatment of SARS-CoV-2 for their effectiveness in preventing severe or long COVID-19. Decentralized strategies included HIPAA-compliant electronic screening and consenting, prepacking investigational product to accelerate delivery after randomization, and remotely confirming participant-reported outcomes. Of the 1417 individuals with the intention-to-treat sample, the remote nature of the study caused an additional 94 participants to not take any doses of study drug. Therefore, 1323 participants were in the modified intention-to-treat sample, which was the a priori primary study sample. Only 1.4% of participants were lost to follow-up. Decentralized strategies facilitated the successful completion of the COVID-OUT trial without any in-person contact by expediting intervention delivery, expanding trial access geographically, limiting contagion exposure, and making it easy for participants to complete follow-up visits. Remotely completed consent and follow-up facilitated enrollment.

A causal roadmap for generating high-quality real-world evidence.

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers; three companion papers demonstrate applications of the Causal Roadmap for specific use cases.

Mitochondrial metabolites predict adverse cardiovascular events in individuals with diabetes.

Metabolic mechanisms underlying the heterogeneity of major adverse cardiovascular (CV) event (MACE) risk in individuals with type 2 diabetes mellitus (T2D) remain unclear. We hypothesized that circulating metabolites reflecting mitochondrial dysfunction predict incident MACE in T2D. Targeted mass-spectrometry profiling of 60 metabolites was performed on baseline plasma samples from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS; discovery cohort) and Exenatide Study of Cardiovascular Event Lowering (EXSCEL; validation cohort) biomarker substudy cohorts. A principal components analysis metabolite factor comprising medium-chain acylcarnitines (MCACs) was associated with MACE in TECOS and validated in EXSCEL, with higher levels associated with higher MACE risk. Meta-analysis showed that long-chain acylcarnitines (LCACs) and dicarboxylacylcarnitines were also associated with MACE. Metabolites remained associated with MACE in multivariate models and favorably changed with exenatide therapy. A third cohort (Cardiac Catheterization Genetics [CATHGEN]) with T2D was assessed to determine whether these metabolites improved discriminative capability of multivariate models for MACE. Nine metabolites (MCACs and LCACs and 1 dicarboxylacylcarnitine) were associated with time to MACE in the CATHGEN cohort. Addition of these metabolites to clinical models minimally improved the discriminative capability for MACE but did significantly down reclassify risk. Thus, metabolites reporting on dysregulated mitochondrial fatty acid oxidation are present in higher levels in individuals with T2D who experience subsequent MACE. These biomarkers may improve CV risk prediction models, be therapy responsive, and highlight emerging risk mechanisms.

A framework for assessing clinical trial site readiness.

Clinical trial processes are unnecessarily inefficient and costly, slowing the translation of medical discoveries into treatments for people living with disease. To reduce redundancies and inefficiencies, a group of clinical trial experts developed a framework for clinical trial site readiness based on existing trial site qualifications from sponsors. The site readiness practices are encompassed within six domains: research team, infrastructure, study management, data collection and management, quality oversight, and ethics and safety. Implementation of this framework for clinical trial sites would reduce inefficiencies in trial conduct and help prepare new sites to enter the clinical trials enterprise, with the potential to improve the reach of clinical trials to underserved communities. Moreover, the framework holds benefits for trial sponsors, contract research organizations, trade associations, trial participants, and the public. For novice sites considering future trials, we provide a framework for site preparation and the engagement of stakeholders. For experienced sites, the framework can be used to assess current practices and inform and engage sponsors, staff, and participants. Details in the supplementary materials provide easy access to key regulatory documents and resources. Invited perspective articles provide greater depth from a systems, DEIA (diversity, equity, inclusion, and accessibility) and decentralized trials perspective.

Use of comprehensive recruitment strategies in the glycemia reduction approaches in diabetes: A comparative effectiveness study (GRADE) multi-center clinical trial.

BACKGROUND/AIMS: We present and describe recruitment strategies implemented from 2013 to 2017 across 45 clinical sites in the United States, participating in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study, an unmasked, randomized controlled trial evaluating four glucose-lowering medications added to metformin in individuals with type 2 diabetes mellitus (duration of diabetes <10 years). We examined the yield of participants recruited through Electronic Health Records systems compared to traditional recruitment methods to leverage access to type 2 diabetes patients in primary care. METHODS: Site selection criteria included availability of the study population, geographic representation, the ability to recruit and retain a diverse pool of participants including traditionally underrepresented groups, and prior site research experience in diabetes clinical trials. Recruitment initiatives were employed to support and monitor recruitment, such as creation of a Recruitment and Retention Committee, development of criteria for Electronic Health Record systems queries, conduct of remote site visits, development of a public screening website, and other central and local initiatives. Notably, the study supported a dedicated recruitment coordinator at each site to manage local recruitment and facilitate screening of potential participants identified by Electronic Health Record systems. RESULTS: The study achieved the enrollment goal of 5000 participants, meeting its target with Black/African American (20%), Hispanic/Latino (18%), and age ≧60 years (42%) subgroups but not with women (36%). Recruitment required 1 year more than the 3 years originally planned. Sites included academic hospitals, integrated health systems, and Veterans Affairs Medical Centers. Participants were enrolled through Electronic Health Record queries (68%), physician referral (13%), traditional mail outreach (7%), TV, radio, flyers, and Internet (7%), and other strategies (5%). Early implementation of targeted Electronic Health Record queries yielded a greater number of eligible participants compared to other recruitment methods. Efforts over time increasingly emphasized engagement with primary care networks. CONCLUSION: Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness successfully recruited a diverse study population with relatively new onset of type 2 diabetes mellitus, relying to a large extent on the use of Electronic Health Record to screen potential participants. A comprehensive approach to recruitment with frequent monitoring was critical to meet the recruitment goal.

Metformin reduces SARS-CoV-2 in a Phase 3 Randomized Placebo Controlled Clinical Trial.

Current antiviral treatment options for SARS-CoV-2 infections are not available globally, cannot be used with many medications, and are limited to virus-specific targets.1-3 Biophysical modeling of SARS-CoV-2 replication predicted that protein translation is an especially attractive target for antiviral therapy.4 Literature review identified metformin, widely known as a treatment for diabetes, as a potential suppressor of protein translation via targeting of the host mTor pathway.5 In vitro, metformin has antiviral activity against RNA viruses including SARS-CoV-2.6,7 In the COVID-OUT phase 3, randomized, placebo-controlled trial of outpatient treatment of COVID-19, metformin had a 42% reduction in ER visits/hospitalizations/death through 14 days; a 58% reduction in hospitalizations/death through 28 days, and a 42% reduction in Long COVID through 10 months.8,9 Here we show viral load analysis of specimens collected in the COVID-OUT trial that the mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95%CI, -1.05 to -0.06, p=0.027) while there was no virologic effect for ivermectin or fluvoxamine vs placebo. The metformin effect was consistent across subgroups and with emerging data.10,11 Our results demonstrate, consistent with model predictions, that a safe, widely available,12 well-tolerated, and inexpensive oral medication, metformin, can be repurposed to significantly reduce SARS-CoV-2 viral load.