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Would you like to learn more about drug clearance and how in-vitro to in-vivo translation generates insights about liver metabolism in drug development? We explain ins and outs of in-vitro to in-vivo correlation to predict human drug clearance in our latest article.

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Does in-vitro to in-vivo correlation deliver metabolic information in the liver?

Pharmacokinetic studies are an integral part of drug development. Drug development consists of many phases and types of studies including in-vitro assays, which may be cell or pure-protein based, and in-vivo (live animal) and clinical studies (involving human volunteers). Human pharmacokinetics are predicted by translating the information on the metabolism of the drug in animals to humans. Thus, with smart use of preclinical data and utilization of in silico modeling and simulations, drug developers can optimize clinical assessment, including experimental PK studies. This data utilization saves time, financial resources and avoids unnecessary exposure of volunteers to drugs in the development process. It also enables more efficient use of animal studies.

Drug clearance (CL) is often translated from animal to human. Clearance is the process in which a drug is removed from the systemic circulation, typically by metabolism and excretion. An example of an approach to predict human CL is using in-vitro to in-vivo correlation (IV-IVc), which can be very insightful for small molecules, that are typically cleared through the liver (metabolism) and/or through the kidneys (excretion).

What is IV-IVc? IV-IVc uses in-vitro data on the metabolic elements of the liver (hepatocytes or derived microsomal preparations) from multiple species, such as rats, dogs, mini-pigs and cynomolgus monkeys. The metabolism in hepatocytes is first scaled using hepatocellularity (the number of hepatocytes per unit tissue mass) and the liver weight to calculate the intrinsic clearance (CLint), i.e. the clearance based on the metabolic activity of the hepatocytes. Next, established models, such as the well-stirred model, are used to predict the effective liver clearance (CLhep) from CLint. Each model is associated with its own assumptions. The well stirred liver model for instance, assumes that the liver is one homogeneous compartment, without a drug concentration gradient in the liver. Therefore, the metabolic rate is taken to be equal everywhere in the liver. The formula for CLhep using the well-stirred liver model reads

CLhep = Q * CLint / (Q + CLint),

where Q is the liver blood flow rate (we ignore aspecific drug binding here to keep it simpler). Once the predicted CLhep is calculated, it is compared to the observed total in-vivo (animal) CL from PK studies. This is the actual in-vitro to in-vivo correlation! This correlation is performed for multiple species, ideally with a wide range of body weights.

How does one interpret the outcomes? A high correlation in multiple species provides confidence for the human prediction of total CL. Total body CL is then probably highly dependent on hepatic CL. Conversely, if the correlation is poor, total CL may depend also on non-hepatic CL, such as degradation by plasma esterases or an important first-pass effect. At PD-value, we perform IV-IVcs and it has always been insightful for our clients to have these relatively quick and less complicated assessments. Although the prediction based on the correlation is not always perfect, for example when the observed CL is much higher than that predicted using IV-IVc, the outcome can provide insight into the clearance and drug mechanism under consideration and guide further drug development. In short: IV-IVc is a practical and cost-effective tool in drug development!