{'fraction_non_alphanumeric': 0.02358490566037736, 'fraction_numerical': 0.0010482180293501049, 'mean_word_length': 5.158064516129032, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Prediction of drug concentration-time data in humans from animals: a comparison of three methods

The main objective of this work is to evaluate three methods to predict concentration-time data of drugs in humans in a multi-compartment system using animal pharmacokinetic parameters following intravenous administration. The prediction of concentration-time data in humans in a multi-compartment system was based on two proposed methods of Mordenti. The third method was based on the assumption that all drugs follow a single-compartment system. Ten drugs from the literature were chosen that were described by two-compartment model in both human and animals. Two-compartment model parameters (CL, Vc, Vss, Vβ, α, A, β and B) of at least 3 animals were scaled to humans and then were used to predict plasma concentrations-time data in humans. Allometrically scaled pharmacokinetic parameters from animals were also used to predict human profile using one-compartment model as a comparison. The results indicated that in a multi-compartment system, application of pharmacokinetic constants provided better prediction of concentration-time data in humans than the assumption that all drugs follow a single-compartment model. Both the proposed methods of Mordenti provided almost similar concentration-time profiles for most of the drugs. For some drugs, predicted α values were substantially higher than the observed values. This prediction error in α resulted in under-prediction of drug concentrations in distribution phase. In order to reduce the prediction error in α, Waijma’s method for the prediction of α was modified which resulted in an improved prediction of concentration-time data in humans. Overall, Mordenti’s proposed 2 methods and where necessary by modifying Waijma’s method for the prediction of α can be used for reasonably accurate prediction of concentration-time data of drugs in humans.