In medicine, one size doesn’t fit all and, despite rigorous testing, there is often no way to predict how an individual patient will react to a particular drug. The aim of personalised prescribing is to be able match the right dose of the right drug to the right patient. Although the study of pharmacogenomics – which looks at the influence of the genetic background of the patient on drug efficacy and/or toxicity – shows promise in predicting how different people will respond to a particular drug, it is increasingly being recognised that other factors are also important in determining individual responses. Scientists at Pfizer Research and Development and Imperial College London have previously shown in animal studies that, as well as genetic variations in metabolic pathways, differences in environmental factors also play a role in determining the safety and efficacy of drugs. In an extension of their earlier work, the researchers have now shown that this combined ‘pharmacometabonomic’ approach is also relevant to human patients. The new study used 1HNMR spectroscopy to evaluate the metabolic fate of a single 1g dose of paracetamol (acetaminophen) against the background of a pre-dose urinary metabolite profile in a group of 99 healthy male volunteers aged 18-64. They found that individuals with high pre-dose levels of p-cresol sulphate had low post-dose ratios of paracetamol sulphate to paracetamol glucuronide. p-Cresol is produced from tyrosine by bacteria in the gut and is then converted to the sulphate by the cytosolic sulphotransferase, SULT1A1, using 3-phosphoadenosine 5-phosphosulphate as cofactor. Since paracetamol is a substrate for the same enzyme-cofactor pair, competition by endogenous p-cresol reduces the amount of paracetamol sulphate. Although it remains to be seen whether these findings could explain adverse reactions to paracetamol, sulphonation plays a role in the excretion of many drugs and their hydroxylated metabolites and production of p-cresol in the gut could influence the metabolism, and hence safety and efficacy, of all of these.
Further studies are needed to determine whether an association between pre-dose urinary metabolite profiles and drug metabolism is seen in larger human populations but, if so, the authors suggest that gut bacteria could become the principal targets of future therapies or could be manipulated to improve drug treatment outcomes. The study is published in the Proceedings of the National Academy of Sciences.
Although the study clearly shows that pharmacometabonomics could have value in optimising individual treatments, as with pharmacogenomic profiling, the logistics of collecting and storing personal data upfront so that prescribing is not delayed will be a formidable hurdle.
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It is very well known that Clotting Factor Concentrates display high inter-patient variability in term of In Vivo Recovery, Clearance, Half Life, Volume of distribution among the haemophilia A or B patients. Individualization of replacement therapy was claimed since 1984 by my working group (Messori A et al., J Clin Hosp Pharm 1984, Jun 9 (2): 95-103). Only recently this issue became popular among haemophilia treaters. Population PK, modelling, and Bayesian compromise are going to be implemented in our clinical practice because, I agree, one size doesn’t fit all!