Drug discovery and drug development is a very lengthy process which takes between 10 to 15 years. It is one of processes where you get more failures than success. It takes more than 2.6 $ billion to develop a new drug and bring it to the market to address specific type of unmet patient needs and that is after the molecule has passed different tests including animals. There is 92% failure rate when it goes into humans after the molecule has been tested in animals and therefore, this makes the process not only lengthy but also risky.
Furthermore, Human biology is a very complex aspect during drug development because even after sequencing entire human genome a small fraction of human biology is understood. There are more than forty trillions of cells in human body and above one trillions of molecules in each cell and this complexity is astonishing. All these challenges that are encountered during R&D of new drug have made Biopharmaceutical industries think differently in finding new ways to address those problems. Unprecedented approach of using AI in re-imagining R&D of new drug was the solution.
Recent advances in artificial intelligence (AI) may help in changing the narrative and accelerate and improve pharmaceutical R&D of new drug. AI and Machine learning help Drug discovery and Development in several ways including; identifying drug targets, finding good molecules from data libraries, suggestion of chemical modification, clinical trials and so on.
Nowadays world leading Biopharmaceutical and biotechnology companies have started to sign significant deals with Artificial-Intelligence (AI) companies to implement AI in drug discovery. For instance, Pfizer is using IBM Watson, to improve its search for immune-oncology drugs. Sanofi has signed a deal to use UK Start-up Exscientia’s artificial-intelligence (AI) platform to hunt for metabolic-disease therapies and Novartis is using AI system from Microsoft company in its AI innovation lab to empower and accelerate discoveries of transformative medicines for patients. Most advanced biopharmaceutical companies have similar collaborations.
This cutting-edge AI system is inevitable since it has started showing promising imperative inputs in drug discovery including but not limited to; Acceleration of compound testing and improved accuracy and reproducibility which result in quicker, cheaper and most-effective drug discovery.
AI in drug discovery is becoming increasingly important since it is solving those diseases with unmet needs, for instance this is untold opportunities to those patients with rare diseases. Beside, using AI in drug discovery will bring also challenges to those early-career researchers including pharmacists since AI system apply some Automation (Robots). It is in this regard those early-career researchers and future young researchers need to be familiar with AI and acquire some set of skills to meet tomorrow’s job market.
- Alex Zhavoronkov. Artificial Intelligence for Drug Discovery, Biomarker Development, and Generation of Novel Chemistry. Mol. pharmaceutical 2018, 15, 4311-4313.
- Nic Fleming. “How artificial intelligence is changing drug discovery”. Nature, vol. 557, no. 7706, 2018, p. S55+.
Accessed at 24/03/2020