Drug Discovery Process
Drug Discovery Process 💊
Drug discovery is an expensive💸, time consuming 🕖 and risky 💣 process consisting of many stages. These stages and the amount of time these stages take can be seen in the figure. I’ll describe the phases briefly.
Early Drug Discovery 💡
Drug discovery starts with identification of a target for a drug to act on. Then, this target is validated by demonstrating that it is involved in the disease and the modulation of the target is likely to have a therapeutic effect. This is followed by searching of molecules showing activity against this target. Promising molecules called leads are chosen and optimized for certain physicochemical attributes and potency against the target.
Preclinical Studies 🔍
Drug candidates are investigated in this stage through in vitro and in vivo experiments. These molecules are firstly tested in vitro (outside of living organisms) and the efficacy and the toxicity of the compounds are determined. However, how these chemicals could affect organisms can only be shown determined by in vivo tests involving animal subjects 😟 The aim in this stage is to detect serious side effects of the candidates.
Clinical Phases 👩👨👨
Clinical trials are where the drug candidates tested on human subjects. The trials start with a small group of people and as the drug’s side effects are detected, the experiments continue with larger and broader groups. The goal of these trials is to detect side effects of the drug on humans and collect evidences for the efficacy and safety of the drug.
Review & Approval ❔
Once clinical trials show convincing results, application for approval is made to corresponding authorities. The authorities examine the evidences for this drug and assess the benefits and risks of the drug. If the risks are acceptable, the drug is approved and manufactured.
Post Marketing Monitoring
The drug discovery process never ends! After the drug is approved and used in population, the safety of the drug is continuously monitored in case of unknown side effects.
References
Gökçe Uludoğan
Teaching Assistant and PhD Student at Computer Engineering
My research interests include deep learning, cheminformatics and natural language processing.