Target assessment with genetic polymorphisms
Please bear with me for a long (but interesting!) story. Bempedoic acid (Esperion) is an inhibitor of ATP citrate lyase (ACLY), an enzyme in the cholesterol synthesis pathway (upstream of HMG-CoA reductase, the target of statins). In a study of 2,230 patients at high risk for cardiovascular events, on maximum statin therapy, and LDL > 70 (basically the PCSK9 target population), bempedoic acid was well tolerated and lowered the LDL by around 16% – a substantial effect. This would potentially position bempedoic acid, an oral drug, to take on the parenteral PCSK9 inhibitors as main backup drug for lipid lowering if longer studies show a reduction in cardiovascular events. There was, however, a fly in the ointment: 13 people died in the treatment group (N=1,487) while only 2 died in the placebo group (N=742). Although this is not statistically significant, it must have caused considerable consternation at the time of unblinding. Also bothersome was that 5 of the deaths in the treatment group were due to cancer (vs. 0 in the placebo group, again not statistically significant). What to do to lift this dark cloud?
Here comes the clever part. In parallel, Esperion had funded a study mining the data from a very large UK repository combining genomic data and health data. Among other things, they identified 9 naturally occurring variants of ACLY (the gene for the enzyme targeted by bempedoic acid) which influence the activity of ACLY. Using this information, they were able to design an ACLY genetic score that is (a) correlated with LDL cholesterol levels, (b) correlated with the incidence of coronary artery disease, (c) not correlated with the incidence of cancer. That gives confidence that 1) bempedoic acid is likely to have a beneficial impact on cardiovascular disease and 2) that inhibiting ACLY is not likely to be cancer-causing (although it is still possible that bempedoic could be oncogenic through an unknown off-target effect). Beyond this specific case, this is an example of a potentially very powerful technique to derisk drug R&D for a given target. The recipe is to discover population polymorphisms (most genes have them) of the intended target and use them as a natural experiment of potential drug activity. It is a more subtle extension of a more traditional method of finding single disease-causing or protective mutations, but it should have much broader applicability and it has the potential to become a standard step of drug R&D.
Safety and Efficacy of Bempedoic Acid to Reduce LDL Cholesterol (subscriber access); Mendelian Randomization Study of ACLY and Cardiovascular Disease (free access); Human Genetics and Drug Development (subscriber access)
Pembro wins again
Nivolumab (Opdivo, BMS) may have been first, and same class agents like avelumab (Bavencio, Pfizer/Merck KGaA) numerous, but, in the fight to dominate PD(L)-1 inhibition, pembrolizumab (Keytruda, Merck), is winning with insolent good fortune. In kidney cancer, nivolumab, avelumab, and pembrolizumab have all shown significant clinical benefit over the previous standard of care with sunitinib (Sutent, Pfizer). However, only pembrolizumab showed a statistically significant survival benefit. A part of statistical luck, a part of good molecule, a part of clever clinical development design and you have the leader in the field. When the dust settles, it would of great interest to figure which mattered more. Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma; Pembrolizumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma; Combination Therapy as First-Line Treatment in Metastatic Renal-Cell Carcinoma (subscriber access)
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