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Amid a global pandemic, the US Food and Drug Administration (FDA) remained relatively active, approving 55novel molecular entities (NMEs) in 2020, the third highest annual rate recorded. Orphan approvals also surged, capturing 60% of NMEs introduced during 2020, as did the number of NMEs approved using a priority review. The pandemic did appear to impact one recent trend, and in a paradoxically encouraging way. Escalating rates of consolidation slowed in 2020, with only 102 companies lost, down by two-thirds over the rate in 2019. This leaves 2000 extant clinical-stage pharmaceutical companies. When limiting this analysis to companies contributing to the research and development (R&D) of an approved drug, eight were lost, leaving 144 extant.

Nonalcoholic steatohepatitis (NASH) is emerging as a major public health issue for the 21st century and is associated with significant liver-related morbidity and mortality. At present, there are no approved drug therapies for NASH. Consequently, NASH has become the focus of significant public and private research and development. In this review, we highlight the research and development (R&D) challenges and opportunities in this emerging therapeutic area. In particular, we consider the impact of the development of new biomarker strategies on clinical trial execution and design, and the positioning of single and combination therapies in future approaches to the treatment of NASH.

Personalized drug screening (PDS) of approved drug libraries enables rapid development of specific small-molecule therapies for individual patients. With a multidisciplinary team including clinicians, researchers, ethicists, informaticians and regulatory professionals, patient treatment can be optimized with greater efficacy and fewer adverse effects by using PDS as an approach to find remedies. In addition, PDS has the potential to rapidly identify therapeutics for a patient suffering from a disease without an existing therapy. From cancer to bacterial infections, we review specific maladies addressed with PDS campaigns. We predict that PDS combined with personal genomic analyses will contribute to the development of future precision medicine endeavors.

Pharmacogenomics (PGx), studying the relationship between drug response and genetic makeup of an individual, is accelerating advances in precision medicine. The FDA includes PGx information in the labeling of approved drugs to better inform on their safety and effectiveness. We herein present a summary of PGx information found in 261 prescription drug labeling documents by querying the publicly available FDALabel database. A total of 362 drug–biomarker pairs (DBPs) were identified. We profiled DBPs using frequency of the biomarkers and their therapeutic classes. Four categories of applications (indication, safety, dosing and information) were discussed according to information in labeling. This analysis facilitates better understanding, utilization and translation of PGx information in drug labeling among researchers, healthcare professionals and the public.

In the USA, drugs are approved by the FDA by three main regulatory pathways: (i) 505(b)(1) new drug applications (NDAs); (ii) 505(b)(2) NDAs; and (iii) 505(j) abbreviated NDAs (ANDAs). The appropriate pathway depends on the active ingredient, already approved drug products, drug formulation, clinical indication, route of exposure, among other factors. The 505(b)(2) NDA pathway is a regulatory approval pathway that allows sponsors to use existing public data in lieu of conducting studies; thus, potentially offering significant drug development and marketing advantages. Nonclinical testing programs for 505(b)(2) submissions are often reduced and, in some cases, are not even required. This paper provides an overview of the 505(b)(2) regulatory pathway with a focus on how nonclinical programs can be streamlined and accelerated.

Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development.