The history and future of population pharmacokinetic analysis in drug development

The analysis of pharmacokinetic data has been in a constant state of evolution since the introduction of the term pharmacokinetics. Early work focused on mechanistic understanding of the absorption, distribution, metabolism and excretion of drug products.The introduction of non-linear mixed effects models to perform population pharmacokinetic analysis initiated a paradigm shift. The application of these models represented a major shift in evaluating variability in pharmacokinetic parameters across a population of subjects.While technological advancements in computing power have fueled the growth of population pharmacokinetics in drug development efforts, there remain many challenges in reducing the time required to incorporate these learnings into a model-informed development process. These challenges exist because of expanding datasets, increased number of diagnostics, and more complex mathematical models.New machine learning tools may be potential solutions for these challenges. These new methodologies include genetic algorithms for model selection, machine learning algorithms for covariate selection, and deep learning models for pharmacokinetic and pharmacodynamic data. These new methods promise the potential for less bias, faster analysis times, and the ability to integrate more data.While questions remain regarding the ability of these models to extrapolate accurately, continued research in this area is expected to address these questions.

Concept and utility of population pharmacokinetic and pharmacokinetic/pharmacodynamic models in drug development and clinical practice

Due to frequent clinical trial failures and consequently fewer new drug approvals, the need for improvement in drug development has, to a certain extent, been met using model-based drug development. Pharmacometrics is a part of pharmacology that quantifies drug behaviour, treatment response and disease progression based on different models (pharmacokinetic - PK, pharmacodynamic - PD, PK/PD models, etc.) and simulations. Regulatory bodies (European Medicines Agency, Food and Drug Administration) encourage the use of modelling and simulations to facilitate decision-making throughout all drug development phases. Moreover, the identification of factors that contribute to variability provides a basis for dose individualisation in routine clinical practice. This review summarises current knowledge regarding the application of pharmacometrics in drug development and clinical practice with emphasis on the population modelling approach.

An improved LC-MS/MS method for determination of docetaxel and its application to population pharmacokinetic study in Chinese cancer patients

Because of its unpredictable side effects and efficacy, the anticancer drug docetaxel (DTX) requires improved characterisation of its pharmacokinetic profiles through population pharmacokinetic studies. A sensitive and rugged LC-MS/MS method for the detection of DTX in human plasma was developed and optimised using paclitaxel as an internal standard (IS). The plasma samples underwent rapid extraction using hybrid solid-phase extraction-protein precipitation. The analyte and IS were separated with an isocratic system on a Zorbax Eclipse Plus C₁₈ column using water containing 0.05% acetic acid along with 20 μM of sodium acetate and methanol (30/70, v/v) as the mobile phase. Quantification was performed using a triple quadrupole mass spectrometer through multiple reaction monitoring in positive mode, using the m/z 830.3 → 548.8 and m/z 876.3 → 307.7 transitions for DTX and paclitaxel, respectively. The range of the calibration curve was 1-500 ng/mL for DTX, and the linear correlation coefficient was >0.99. The accuracies ranged from -4.6 to 4.2%, and the precision was no higher than 7.0% for the analytes. No significant matrix effect was observed. Both DTX and the IS showed considerable recovery. This method was finally applied to the establishment of a population pharmacokinetic model to optimise the clinical use of DTX.

Current and promising novel drug candidates against visceral leishmaniasis

Leishmaniasis is a group of zoonotic diseases caused by a trypanosomatid parasite mostly in impoverished populations of low-income countries. In their different forms, leishmaniasis is prevalent in more than 98 countries all over the world and approximately 360-million people are at risk. Since no vaccine is currently available to prevent any form of the disease, the control strategy of leishmaniasis mainly relies on early case detection followed by adequate pharmacological treatment that may improve the prognosis and can reduce transmission. A handful of compounds and formulations are available for the treatment of leishmaniasis in humans, but only few of them are currently in use since most of these agents are associated with toxicity problems such as nephrotoxicity and cardiotoxicity in addition to resistance problems. In recent decades, very few novel drugs, new formulations of standard drugs or combinations of them have been approved against leishmaniasis. This review highlights the current drugs and combinations that are used medical practice and recent advances in new treatments against leishmaniasis that were pointed out in the recent 2nd Conference, Global Challenges in Neglected Tropical Diseases, held in San Juan, Puerto Rico in June 2018, emphasizing the plethora of new families of molecules that are bridging the gap between preclinical and first-in-man trials in next future.

In silico assessment of biomedical products: The conundrum of rare but not so rare events in two case studies

In silico clinical trials, defined as "The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention," have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients' phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern.

Pharmacokinetics and biodistribution of squalene-containing emulsion adjuvant following intramuscular injection of H5N1 influenza vaccine in mice

Squalene is a component of oil-in-water emulsion adjuvants developed for potential use in some influenza vaccines. The biodistribution of the squalene-containing emulsion adjuvant (AddaVax™) alone and as part of complete H5N1 vaccine was quantified in mechanistically and toxicologically relevant target tissues up to 336 h (14 days) following injection into quadriceps muscle. At 1 h, about 55% of the intramuscularly injected dose of squalene was detected in the local quadriceps muscles and this decreased to 26% at 48 h. Twenty-four hours after the injection, approximately 5%, 1%, and 0.6% of the injected dose was detected in inguinal fat, draining lymph nodes, and sciatic nerve, respectively. The peak concentration for kidney, brain, spinal cord, bone marrow, and spleen was each less than 1% of the injected dose, and H5N1 antigen did not significantly alter the biodistribution of squalene to these tissues. The area-under-blood-concentration curve (AUC) and peak blood concentration (Cmax) of squalene were slightly higher (20-25%) in the presence of H5N1 antigen. A population pharmacokinetic model-based statistical analysis identified body weight and H5N1 antigen as covariates influencing the clearance of squalene. The results contribute to the body of knowledge informing benefit-risk analyses of squalene-containing emulsion vaccine adjuvants.

Dosage assessment of valnemulin in pigs based on population pharmacokinetic and Monte Carlo simulation

To estimate the valnemulin pharmacokinetic profile in a swine population and to assess a dosage regimen for increasing the likelihood of optimization. This study was, respectively, performed in 22 sows culled by p.o. administration and in 80 growing-finishing pigs by i.v. administration at a single dose of 10 mg/kg to develop a population pharmacokinetic model and Monte Carlo simulation. The relationships among the plasma concentration, dose, and time of valnemulin in pigs were illustrated as C(i,v) = X(0 )(8.4191 × 10(-4) × e(-0.2371t) + 1.2788 × 10(-5) × e(-0.0069t)) after i.v. and C(p.o) = X(0) (-8.4964 × 10(-4) × e(-0.5840t) + 8.4195 × e(-0.2371t) + 7.6869 × 10(-6) × e(-0.0069t)) after p.o. Monte Carlo simulation showed that T(>MIC) was more than 24 h when a single daily dosage at 13.5 mg/kg BW in pigs was administrated by p.o., and MIC was 0.031 mg/L. It was concluded that the current dosage regimen at 10-12 mg/kg BW led to valnemulin underexposure if the MIC was more than 0.031 mg/L and could increase the risk of treatment failure and/or drug resistance.