The history and future of population pharmacokinetic analysis in drug development

1. 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.2. 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.3. While technological advancements in computing power have feuled 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.4. 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.5. While questions remain regarding the ability of these models to extrapolate accurately, continued research in this area is expected to address these questions.

Harnessing Clinical Trial and Real-World Data Towards an Understanding of Sex Effects on Drug Pharmacokinetics, Pharmacodynamics and Efficacy

Increasing clinical data on sex-related differences in drug efficacy and toxicity has highlighted the importance of understanding the impact of sex on drug pharmacokinetics and pharmacodynamics. Intrinsic differences between males and females, such as different CYP enzyme activity, drug transporter expression or levels of sex hormones can all contribute to different responses to medications. However, most studies do not include sex-specific investigations, leading to lack of sex-disaggregated pharmacokinetic and pharmacodynamic data. Based available literature, the potential influence of sex on exposure-response relationship has not been fully explored for many drugs used in clinical practice, though population-based pharmacokinetic/pharmacodynamic modelling is well-placed to explore this effect. The aim of this review is to highlight existing knowledge gaps regarding the effect of sex on clinical outcomes, thereby proposing future research direction for the drugs with significant sex differences. Based on evaluated drugs encompassing all therapeutic areas, 25 drugs demonstrated a clinically meaningful sex differences in drug exposure (characterised by ≥ 50% change in drug exposure) and this altered PK was correlated with differential response.

A semi-mechanistic pharmacokinetic model of saquinavir combined with itraconazole in HIV-1-positive patients

The mechanism of drug-drug interaction between saquinavir, a protease inhibitor used effectively for HIV/AIDS treatment, and itraconazole, an azole antifungal agent, is hypothesized to involve competitive inhibition at CYP3A4 enzyme, an important drug metabolizing enzyme in humans. The resulting interaction between these CYP3A4 substrates can be utilized clinically as a pharmacokinetic booster for prolonging saquinavir dosing regimen and/or decreasing saquinavir dose requirement in HIV/AIDS patients. To quantitatively describe this specific drug-drug interaction, based on the existing data, we aimed to develop a mathematical model incorporated with the competitive inhibition phenomena. PlotDigitizer was used to extract data from literature. Advance Continuous Simulating Language Extreme (ACSLX), a FORTRAN-based computer program, was employed as our developing tool. Our computer model simulations could successfully describe concentration-time course of saquinavir from selected pharmacokinetic studies in HIV-1-positive patients. To extend the model's utility as an aid in saquinavir dosage regimens, the developed model may be applied to other HIV/AIDS patients in genuine clinical settings.

Antiretroviral drugs induce oxidative stress and neuronal damage in the central nervous system

HIV-associated neurocognitive disorder (HAND), characterized by a wide spectrum of behavioral, cognitive, and motor dysfunctions, continues to affect approximately 50 % of HIV(+) patients despite the success of combination antiretroviral drug therapy (cART) in the periphery. Of note, potential toxicity of antiretroviral drugs in the central nervous system (CNS) remains remarkably underexplored and may contribute to the persistence of HAND in the cART era. Previous studies have shown antiretrovirals (ARVs) to be neurotoxic in the peripheral nervous system in vivo and in peripheral neurons in vitro. Alterations in lipid and protein metabolism, mitochondrial damage, and oxidative stress all play a role in peripheral ARV neurotoxicity. We hypothesized that ARVs also induce cellular stresses in the CNS, ultimately leading to neuronal damage and contributing to the changing clinical and pathological picture seen in HIV-positive patients in the cART era. In this report, we show that ARVs are neurotoxic in the CNS in both pigtail macaques and rats in vivo. Furthermore, in vitro, ARVs lead to accumulation of reactive oxygen species (ROS), and ultimately induction of neuronal damage and death. Whereas ARVs alone caused some activation of the endogenous antioxidant response in vitro, augmentation of this response by a fumaric acid ester, monomethyl fumarate (MMF), blocked ARV-induced ROS generation, and neuronal damage/death. These findings implicate oxidative stress as a contributor to the underlying mechanisms of ARV-induced neurotoxicity and will provide an access point for adjunctive therapies to complement ARV therapy and reduce neurotoxicity in this patient population.

Nanosolvated microtubule-modulating chemotherapeutics: a case-to-case study

About 10% of the drugs in the preclinical stage are poorly soluble, 40% of the drugs in the pipeline have poor solubility, and even 60% of drugs coming directly from synthesis have aqueous solubility below 0.1 mg/ml. Out of the research around, 40% of lipophilic drug candidates fail to reach the market despite having potential pharmacodynamic activities. Microtubule-modulating chemotherapeutics is an important class of cancer chemotherapy. Most chemotherapeutics that belong to this category are plant-derived active constituents, such as vincristine, vinblastine, colchicine, docetaxel, paclitaxel, and noscapinoids. The pKa of a drug considerably affects its solubility in physiological fluids and consequently bioavailability. It usually ranges from 5 to 12 for microtubule-modulating drugs. Hence, the solubility of these drugs in physiological fluids is considerably affected by a change in pH. However, because of unpredictable parameters involved in poor solubility and the low oral bioavailability of these chemotherapeutics during the early phases of drug development, they often have an unusual pharmacokinetic profile. This makes the development process of novel chemotherapeutics slow, inefficient, patient-unfriendly, and very costly, emphasizing a need for more rational approaches on the basis of preclinical concepts. Nanosolvation is a process of increasing the polarity of a hydrophobic molecule either by solvation or cavitization in a hydrophilic macrocycle. The present review therefore focuses on the techniques applied in nanosolvation of microtubule-modulating chemotherapeutics to enhance solubility and bioavailability. The methodologies described will be highly beneficial for anticancer researchers to follow a trend of rational drug development.

Application of population pharmacokinetics for preclinical safety and efficacy studies

From the beginning of the 1980s, population PK has been primarily used in clinical development and only in the last decade has it been convincingly applied in a preclinical setting. Sparse sampling and covariate analyses are key features of preclinical popPK, useful for toxicology and efficacy studies in animals to assemble data obtained from different studies; for describing individual PK and PD; for building mechanistic models; and for performing interspecies scaling-up of disposition and efficacy. Application in disease models, mainly in behavioral and neurological models, allows the quantitative description of PK and PD without frequent blood sampling and recurrent physiological measurements, which are the critical and compromising perturbations of experimental systems. A preclinical population approach to PK and PD, by its versatility and possibility of simulating ‘what if’ scenarios, offers a unique and potent tool in the development of new drugs, in particular biologics.

Nonlinear pharmacokinetics of 5-methoxy-N,N-dimethyltryptamine in mice

5-Methoxy-N,N,-dimethyltryptamine (5-MeO-DMT), an abused serotonergic indolealkylamine drug, was placed into Schedule I controlled substance status in the United States as of January 19, 2011. In previous studies, we have shown the impact of monoamine oxidase A and cytochrome P450 2D6 enzymes on 5-MeO-DMT metabolism and pharmacokinetics. The aim of this study was to investigate 5-MeO-DMT pharmacokinetic properties after intravenous or intraperitoneal administration of three different doses (2, 10, and 20 mg/kg) to CYP2D6-humanized (Tg-CYP2D6) and wild-type control mice. Systemic exposure [area under the curve (AUC)] to 5-MeO-DMT was increased nonproportionally with the increase in dose. The existence of nonlinearity in serum 5-MeO-DMT pharmacokinetics was clearly manifested by dose-normalized AUC values, which were approximately 1.5- to 2.0-fold (intravenous) and 1.8- to 2.7-fold (intraperitoneal) higher in wild-type or Tg-CYP2D6 mice dosed with 10 and 20 mg/kg 5-MeO-DMT, respectively, than those in mice treated with 2 mg/kg 5-MeO-DMT. Furthermore, a two-compartment model including first-order absorption, nonlinear (Michaelis-Menten) elimination, and CYP2D6-dependent linear elimination from the central compartment was developed to characterize the intravenous and intraperitoneal pharmacokinetic data for 5-MeO-DMT in wild-type and Tg-CYP2D6 mice. In addition, 5-MeO-DMT was readily detected in mouse brain after drug treatment, and brain 5-MeO-DMT concentrations were also increased nonproportionally with the increase of dose. The results establish a nonlinear pharmacokinetic property for 5-MeO-DMT in mice, suggesting that the risk of 5-MeO-DMT intoxication may be increased nonproportionally at higher doses.