What is Drug Discovery?
Drug discovery refers to the process of identifying a potentially suitable candidate medication that has enough of a desired therapeutic effect to successfully bring it to market. This is the first step in the drug development process, and it uses the stage-gate process throughout.
Before the widespread use of sophisticated software, drug discovery consisted of either learning which active ingredients in known remedies were effective or through serendipity (e.g., penicillin). However, once computers became everyday items and software incorporated artificial intelligence (AI) as a default, drug discovery shifted to complex chemical libraries that simplified and strengthened the process.
It’s no secret that drug development is time-consuming and expensive. It can cost billions of dollars and take more than a decade to bring a new drug to market. As such, conducting proper due diligence such as researching clinical trials, peer-reviewed journals, and meeting drug regulation standards, and obeying patent laws can help minimize losses. Despite this, drug discovery still suffers from a very high rate of attrition for new therapeutic discoveries, making the use of specialized software even more important to limit human error hindering the process.
Other Names for Drug Discovery:
- Drug development
- Discovery and development
- Drug screening
- Drug design
Why is Drug Discovery Important?
Drug discovery is important because it can help treat acute and chronic ailments on both a small and large scale. As organisms’ lifespans lengthen due to increased knowledge of internal medicine, new or more complex diseases and conditions arise, necessitating targeted and effective drugs for therapeutic treatment.
Historically, drug discovery consisted of a serendipitous approach as with penicillin or understanding which ingredient in a traditional remedy was effective for treating an ailment and using it with that specific purpose. Modern drug discovery, on the other hand, supports a far more capital-intensive and structured approach by using AI or innovation intelligence during the process, and can result in discoveries like penicillin being omitted from a vaccine due to allergy.
Drug design is an even more modern form of drug discovery, which uses bioinformatics and computer modeling to design molecules that can match the biological target. In particular, AI is helping reshape drug discovery and becoming a necessity instead of a nice-to-have.
No matter which modern approach to drug discovery is used, all involve a stage-gate process of preclinical research, clinical trials, and obtaining regulatory approval. The entire process, from drug discovery to completed development, can take well over a decade, with costs easily running into the tens of millions or billions. Because of this, using the most specialized software to aid in research and development (R&D) is key. Innovators can reduce human error and reliance on heuristics in favor of big data and machine learning to increase efficiency dramatically.
Despite this, the attrition rate of approved drugs is still very high, leading to many abandoned patent applications on the drug landscape. A keen innovator can use this to their advantage, such as utilizing dedicated platforms that enable them to search for a biosimilar, drug patent expiry, or abandoned application, identify other innovators with overlapping needs, and collaborate in drug discovery to shorten the time and costs involved.