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How the AI revolution can accelerate early drug discovery

Drug Target Review

“AI will not replace drug discovery scientists, but drug discovery scientists who use AI will replace those who don’t” – comment during EFMC meeting 2018 Progressing a drug molecule from concept to commercialisation typically takes 10-15 years and has high associated costs of up to $2 billion per launched drug, if all failures are factored in.

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Metabolism of 2022 FDA approved small molecule drugs PART 2

Metabolite Tales Blog

Deuteration at this position was found to block generation of a less selective primary amide metabolite in vivo and increase metabolic stability. Insights into drug metabolism by cytochromes P450 from modelling studies of CYP2D6-drug interactions. link] [2] Zhang and Tang, 2018. 2018 Sep;8(5):721-732.

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N-glucuronidation: the human element

Metabolite Tales Blog

To curb glucuronidation at that position a gem-dimethyl group was incorporated which not only boosted metabolic stability, but also resulted in increased potency of the final lead compound. Figure 4: Optimisation of an IDO1 inhibitor incorporating installation of a gem-dimethyl group to control glucuronidation of a key hydroxyl group.

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Metabolism of five membered nitrogen containing heterocycles

Metabolite Tales Blog

2018, 26, 965-972 [link] 4a Pharmaceutics, 2022, 14, 1001 [link] 5 Phys. 2018, 61, 5, 2041–205 [link] 9 ACS Chem. 2006 , 34, 145-51 [link] 3 Drug Metab. 1980, 8, 34-38 [link] 4 J. Food Drug Anal. 2000, 2, 195-201 [link] 6 Biochem. 1966 98, 266-277 [link] 7 Metabolites. 2023, 13, 1, 92- [link] 8 J. 2019, 14, 2, 142–16 [link] 10 Chem.

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Breaking C-F bonds in drugs

Metabolite Tales Blog

This was surprising given that replacement of a phenyl with a pyrimidine and fluorination of aryl or heteroaryl rings are techniques often used to increase metabolic stability. Journal of Medicinal Chemistry 2018 61 (23), 10700-10708, [link] [13] Chemical Aspects of Human and Environmental Overload with Fluorine. Elizabeth A.

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We Need Better Benchmarks for Machine Learning in Drug Discovery

Practical Cheminformatics

I wrote more about the problems with this dataset in a Practical Cheminformatics post in 2018. Initially, I would recommend aqueous solubility, membrane permeability, in vitro metabolic stability, and biochemical assays. I have a few ideas. Focus benchmarking efforts on simple, robust, relevant, clearly defined endpoints.

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