With more than 1,500 drugs approved by the Food and Drug Administration (FDA) on the market, the easiest disease targets are already covered (1). Today’s scientists are challenged to find new compounds, acting alone or in combination, on intractable targets to treat multicausal diseases including cancers, metabolic and psychiatric disorders.
The technologies and assays coming to the market enable new avenues in drug discovery creating opportunities to study complex disease mechanisms and find cures for the indications mentioned above.
From the ancient Egypt Pharmacopeia described in Ebers Papyrus until the emergence of high throughput screening (HTS) in the early 1990s, drug discoveries mostly resulted from serendipity, intuition and trial-and-error efforts (forward pharmacology) or from first-generation rational drug design (reverse pharmacology).
The discovery of penicillin from mould secretions reported by Fleming originated from serendipity and intuition (2). The H2 blocker and antacid cimetidine (Tagamet), derived from histamine which is known to promote gastric acid release, is a representative example of a drug developed using reverse pharmacology (3).
The traditional drug discovery approaches used until the end of the 1980s revealed too time-consuming, low-throughput and cost-ineffective by the industry which – relying on automation and second- generation (computer-assisted) rational drug design – started to perform high-throughput screening campaigns of large combichem libraries on purified biological targets.
Despite the increasing complexity of the disease targets to address, HTS campaigns contributed to deliver close to 50% of the total drugs approved by the FDA since 1930. However, the drug attrition rate observed during clinical trials remains high in all therapeutic areas mainly due to a lack of efficacy observed during Phase II-III studies, offsetting some of the HTS benefits (4).
Changing the drug discovery paradigm
The overall efficiency of pharmaceutical research and development (R&D), defined as the ratio of the New Molecular Entities (NMEs) and Biologic License Applications (BLAs) launched as a function of their associated R&D investments, has declined over the last decade (5). To improve the situation, numerous advances were brought to the drug discovery process.
For instance, predictive toxicology concepts were introduced during absorption, distribution, metabolism, elimination and toxicity (ADMET) to fail drug candidates more rapidly and reduce the drug attrition rate related to safety. While toxicity was traditionally assessed using animal models during the late stage of drug development, predictive toxicology required the development of in silico and in vitro methods executable at large scale and sooner in the drug discovery workflow.....
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