The fundamental objective of pharmaceutical research is to develop safe and effective medicines for treating diseases and disorders. This endeavor hinges on understanding how drugs interact with complex biological macromolecules, including proteins, polysaccharides, lipids, and nucleic acids. Historically, proteins have been the primary focus owing to the relative ease of studying drug-protein interactions, facilitating specificity and toxicity prediction (Hopkins & Groom, 2002). At the core of this is "druggability," a target's ability to be therapeutically modulated by chemicals, such as traditional small molecules.

Advancements in genomic science have profoundly reshaped target identification, enhancing our understanding of how genes are linked to diseases and encode proteins. The human genome contains approximately 21,000 protein-coding genes (Willyard, 2018; Hopkins & Groom, 2002; Amaral et al., 2023). These genes identified a substantial number of likely druggable targets, ranging from 3,000 to 10,000 (Drews & Ryser, 1997; Claverie, 2001; Hopkins & Groom, 2002), with approximately 3,000 genes associated with diseases (Rask-Andersen et al., 2011). For a long time, protein products of genes have been the main focus of drug targeting. But advances in molecular medicine have expanded treatment options to encompass genes and their RNA transcripts as well. This growth encompasses other types of treatments, such as gene therapy and therapeutic oligonucleotides, which affect how genes are expressed after they are transcribed (Oprea & Hasselgren, 2017; Welsh, 2025). Identifying and confirming the most effective molecular targets is central to drug development, as it leads to the creation of new treatments. Choosing the right targets is crucial for the pharmaceutical industry, as it significantly impacts the success or failure of research and development projects. By understanding the drug targets approved by the US Food and Drug Administration (FDA), we open the door to a valuable set of real-world data. This insight can help us select future targets and enhance the effectiveness and efficiency of research and development processes (Paul et al., 2010; Swinney & Anthony, 2011; Swinney, 2022).

The mapping of molecular drug targets for approved drugs has a rich history. Early efforts by Drews (1996, 1997) compiled about 500 human molecular targets for small-molecule drugs. Subsequent studies provided varying estimates, reflecting evolving definitions and data sources. Hopkins and Groom (2002) suggested 600–1500 targets; Overington et al. (2006) estimated 324 targets (expanded to 604 genes) for 1065 FDA-approved drugs sourced from the FDA Orange Book and the Center for Biologics Evaluation and Research (CBER) website (for biological drugs). In 2011, Rask-Andersen et al. identified 435 targets for 989 drugs approved between 1982 and 2010. In contrast, Santos et al. (2017) mapped 667 human-genome-derived proteins for 1,194 drugs approved up to 2015. Recently, Brown and Wobst (2021) assessed novel FDA-approved drugs (2010-2019), reporting 378 drugs, averaging 38 drugs annually. Many investigators, including those from the British Pharmacological Society (Alexander et al., 2023), have published a compendium of drug targets for FDA-approved drugs by integrating data from public databases. The variability in these numbers highlights the dynamic nature of the field and the continuous influx of new approvals, underscoring the need for updated analyses. Building on prior efforts, the present review offers a unique and timely contribution by analyzing all the molecular types approved by the FDA's Center for Drug Evaluation and Research (CDER) from 2015-2024. During this 10-year span, the FDA approved 465 drugs, averaging 46.5 drugs annually. The totals for new molecular entities (NMEs) and biologics were 332 (71.4%) and 133 (28.6%) drugs, respectively. Preliminary observations show notable trends: 2018 (59 approvals) and 2023 (55 approvals) were peak years, representing the highest harvest in the FDA's history for this period. These years also had the highest number of biologics approvals, e.g., in 2018, 17 of the 59 approved drugs were biologics. A striking finding from this period is that 73% of the 2018 approvals utilized expedited review pathways, with 19 drugs designated as first-in-class (FIC). This correlation suggests a strong link between regulatory efficiency, innovation, and overall drug approval rates, indicating that expedited pathways facilitate the rapid approval of innovative therapies.

This review presents a detailed analysis of FDA-approved drugs from 2015-2024, with a focus on molecular efficacy and human target activity, organized by therapeutic indication. The assignment of each drug to five prominent target proteins and the top four noncommunicable diseases is derived from FDA prescribing information, the DrugBank database (https://go.drugbank.com/), the Guide to Pharmacology database (https://www.guidetopharmacology.org), Drugs@FDA (2025) (https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm), and scientific literature, enabling exploration of trends within disease areas and privileged protein classes. The analysis also encompasses therapeutic modalities, including NMEs (small-molecules and macromolecules), and biologics. A key aspect of this focused and comprehensive review is examining how the four expedited review pathways (accelerated approval, breakthrough therapy, fast track, and priority review) augment drug approvals, particularly for devastating diseases and areas of unmet medical need, such as orphan indications. Furthermore, the review assesses drug innovation by analyzing emerging trends in FIC and orphan drug designations, and their association with expedited review processes. Most importantly, this review employs an extended analytical framework: the "quartet model," which explores the complex interrelationships among drug, target class, therapeutic area, and disease in drug discovery. This multi-dimensional approach aims to uncover nuanced connections and provide a holistic understanding of drug development trends and innovations.