Interpreting Adverse Signals in Diabetes Drug Development Programs Featured Article: Clifford J. Bailey, Ph.D. Diabetes Care Volume 36: 1-9 July, 2013.

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Interpreting Adverse Signals in Diabetes Drug Development Programs Featured Article: Clifford J. Bailey, Ph.D. Diabetes Care Volume 36: 1-9 July, 2013

PREAPPROVAL CLINICAL TRIALS It takes at least 10 years for a new class of agent to go from molecule to medicine and costs ~$500 million If many unsuccessful drug discovery studies and early development programs are considered, the average approved drug probably reflects $1.3–1.8 billion of investment Individual clinical trials are restricted for patient selection, number, and duration Trials can introduce allocation and ascertainment bias, and they often rely on biomarkers to estimate long-term clinical outcomes Bailey C. J. et al. Diabetes Care 2013;36:1-9

DETERMINING BENEFITS AND RISKS Benefit: unlikely that an agent will be submitted for marketing authorization if it does not meet recognized approvable efficacy criteria In diabetes, the risk perspective is inevitably confounded by emergent comorbid conditions and potential interactions that limit therapeutic choice There is a need for new therapies and better use of existing therapies to address the consequences of protracted glucotoxicity Bailey C. J. et al. Diabetes Care 2013;36:1-9

HYPOGLYCEMIA Treatment with antidiabetic drugs commonly produces mild hypoglycemic symptoms Signs of moderate or severe hypoglycemia and extra risks are well rehearsed in product labeling and education packages Nevertheless, propensity for hypoglycemia forms an integral part of the calculation of acceptable risk for all diabetes pharmacotherapies Bailey C. J. et al. Diabetes Care 2013;36:1-9

WEIGHT CHANGES Escalation in vascular susceptibility that accompanies coexistent diabetes and obesity is an important component of overall risk Rapid weight gain may signal issues other than adiposity, such as fluid retention with thiazolidinediones Rapid initial weight loss during a clinical trial may lead to a detection bias for certain tumors Bailey C. J. et al. Diabetes Care 2013;36:1-9

CARDIOVASCULAR Considerable attention directed toward cardiovascular (CV) risk assessment and minimization Data were analyzed from 42 randomized trials with rosiglitazone, excluding six studies in which there were no CV events Analysis reported that rosiglitazone is associated with an increased odds for myocardial infarction and CV death Rosiglitazone experience prompted the U.S. Food and Drug Association to issue new guidance about CV risk Bailey C. J. et al. Diabetes Care 2013;36:1-9

CANCER Whereas CV events are common in diabetes, cancers are uncommon or rare but modestly increased Detection is often delayed Attributing cause is complicated by familial susceptibility; present and prior obesity; history of exposure to carcinogens, including smoking; and comorbid conditions Allocation factors can also confuse the evidence surrounding malignancies (for example, an uneven randomization for ethnicity, gender, socioeconomic status, and educational or geographical background can significantly influence the occurrence of cancers) Bailey C. J. et al. Diabetes Care 2013;36:1-9

BONE FRACTURES Thiazolidinediones have been associated with declining bone mineral density and increased risk of bone fractures, especially in older women Although thiazolidinediones continue to receive careful clinical investigation, they provide a further example of the importance of preclinical mechanistic studies Bailey C. J. et al. Diabetes Care 2013;36:1-9

CONCLUSIONS A challenge when interpreting adverse signals in clinical trials is the need to extrapolate to a real-world environment where patient populations may be more diverse, prescribers less specialized, and monitoring less conscientious Detection and interpretation of adverse signals during preclinical and clinical stages of drug development inform the benefit-risk assessment that determines suitability for use in real-world situations This review illustrates the difficulties in ascribing causality and evaluating absolute risk, predictability, prevention, and containment Bailey C. J. et al. Diabetes Care 2013;36:1-9