The emerging role of physiologically based pharmacokinetic modelling in solid drug nanoparticle translation☆

ABSTRACT The use of solid drug nanoparticles (SDN) has become an established approach to improve drug delivery, supporting enhancement of oral absorption and long‐acting administration strategies. A broad range of SDNs have been successfully utilised for multiple products and several development programmes are currently underway across different therapeutic areas. With some approaches, a large range of material space is available with diversity in physical characteristics, excipient choice and pharmacological behaviour. The selection of SDN lead candidates is a complex process including a broad range of in vitro and in vivo data, and a better understanding of how physical characteristics relate to performance is required. Physiologically‐based pharmacokinetic (PBPK) modelling is based upon a comprehensive integration of experimental data into a mathematical description of drug distribution, allowing simulation of SDN pharmacokinetics that can be qualified in vivo prior to human prediction. This review aims to provide a description of how PBPK can find application into the development of SDN. Integration of predictive PBPK modelling into SDN development allows a better understanding of the SDN dose‐response relationship, supporting a framework for rational optimisation while reducing the risk of failure in developing safe and effective nanomedicines. Graphical abstract Figure. No caption available.

[1]  J. Meza,et al.  Long-acting parenteral nanoformulated antiretroviral therapy: interest and attitudes of HIV-infected patients. , 2013, Nanomedicine.

[2]  P. Fusar-Poli,et al.  Patients’ and clinicians’ attitude towards long-acting depot antipsychotics in subjects with a first episode of psychosis , 2013, Therapeutic advances in psychopharmacology.

[3]  Darren L. Smith,et al.  Antiretroviral Solid Drug Nanoparticles with Enhanced Oral Bioavailability: Production, Characterization, and In Vitro–In Vivo Correlation , 2014, Advanced healthcare materials.

[4]  D. Podzamczer,et al.  Long-acting intramuscular cabotegravir and rilpivirine in adults with HIV-1 infection (LATTE-2): 96-week results of a randomised, open-label, phase 2b, non-inferiority trial , 2017, The Lancet.

[5]  Marco Siccardi,et al.  Physiologically Based Pharmacokinetic Modelling to Inform Development of Intramuscular Long-Acting Nanoformulations for HIV , 2015, Clinical Pharmacokinetics.

[6]  T. Shapiro,et al.  Long-acting injectable atovaquone nanomedicines for malaria prophylaxis , 2018, Nature Communications.

[7]  Maged M. Costantine,et al.  Physiologic and pharmacokinetic changes in pregnancy , 2014, Front. Pharmacol..

[8]  D. Matsui Current Issues in Pediatric Medication Adherence , 2007, Paediatric drugs.

[9]  Yuichi Sugiyama,et al.  Prediction of Hepatic Clearance in Human From In Vitro Data for Successful Drug Development , 2009, The AAPS Journal.

[10]  M. Gohel,et al.  Current approaches for in vitro drug release study of long acting parenteral formulations. , 2015, Current drug delivery.

[11]  C. Marzolini,et al.  Applications of physiologically based pharmacokinetic modeling for the optimization of anti-infective therapies , 2015, Expert opinion on drug metabolism & toxicology.

[12]  Barrett E. Rabinow,et al.  Nanosuspensions in drug delivery , 2004, Nature Reviews Drug Discovery.

[13]  D. Burgess,et al.  Accelerated in‐vitro release testing methods for extended‐release parenteral dosage forms , 2012, The Journal of pharmacy and pharmacology.

[14]  A J Bailer,et al.  An introduction to the use of physiologically based pharmacokinetic models in risk assessment , 1997, Statistical methods in medical research.

[15]  C. Flexner,et al.  In Silico Dose Prediction for Long-Acting Rilpivirine and Cabotegravir Administration to Children and Adolescents , 2018, Clinical Pharmacokinetics.

[16]  Jingjing Yu,et al.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification , 2015, Drug Metabolism and Disposition.

[17]  A. Zuppa,et al.  Special population considerations and regulatory affairs for clinical research , 2015, Clinical research and regulatory affairs.

[18]  S. Shi,et al.  Age-related changes in pharmacokinetics. , 2011, Current drug metabolism.

[19]  C. Marzolini,et al.  Pharmacokinetic and Pharmacodynamic Analysis of Efavirenz Dose Reduction Using an In Vitro–In Vivo Extrapolation Model , 2012, Clinical pharmacology and therapeutics.

[20]  S. Rannard,et al.  Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate , 2017, Antimicrobial Agents and Chemotherapy.

[21]  Jouni Hirvonen,et al.  Pharmaceutical nanocrystals by nanomilling: critical process parameters, particle fracturing and stabilization methods , 2010, The Journal of pharmacy and pharmacology.

[22]  Min Li,et al.  Physiologically Based Pharmacokinetic (PBPK) Modeling of Pharmaceutical Nanoparticles , 2016, The AAPS Journal.

[23]  David A. Winkler,et al.  The role of quantitative structure-activity relationships (QSAR) in biomolecular discovery , 2002, Briefings Bioinform..

[24]  T. Tan,et al.  Preparation of Azithromycin Nanosuspensions by High Pressure Homogenization and its Physicochemical Characteristics Studies , 2007, Drug development and industrial pharmacy.

[25]  M. Battegay,et al.  Physiologically Based Pharmacokinetic Modeling to Predict Drug–Drug Interactions with Efavirenz Involving Simultaneous Inducing and Inhibitory Effects on Cytochromes , 2017, Clinical Pharmacokinetics.

[26]  Lieven Baert,et al.  Pharmacokinetics and Disposition of Rilpivirine (TMC278) Nanosuspension as a Long-Acting Injectable Antiretroviral Formulation , 2010, Antimicrobial Agents and Chemotherapy.

[27]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[28]  C. Flexner,et al.  Modelling the long-acting administration of anti-tuberculosis agents using PBPK: a proof of concept study. , 2018, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[29]  S. Rannard,et al.  Strengths, weaknesses, opportunities and challenges for long acting injectable therapies: Insights for applications in HIV therapy. , 2016, Advanced drug delivery reviews.

[30]  Marco Siccardi,et al.  Validation of Computational Approaches for Antiretroviral Dose Optimization , 2016, Antimicrobial Agents and Chemotherapy.

[31]  W. Slob,et al.  An improved model to predict physiologically based model parameters and their inter-individual variability from anthropometry , 2012, Critical reviews in toxicology.

[32]  L Aarons,et al.  Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed. , 2005, British journal of clinical pharmacology.

[33]  E. Enioutina,et al.  Pharmacokinetic considerations in the use of antivirals in neonates , 2015, Expert opinion on drug metabolism & toxicology.

[34]  Lulu Wang,et al.  Nanosuspensions of poorly water-soluble drugs prepared by bottom-up technologies. , 2015, International journal of pharmaceutics.

[35]  S. Rosenbaum,et al.  Developmental pharmacokinetics in pediatric populations. , 2014, The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG.

[36]  D. Hazuda,et al.  Long-acting formulations for the treatment of latent tuberculous infection: opportunities and challenges. , 2018, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[37]  Steve Rannard,et al.  Multicomponent Organic Nanoparticles for Fluorescence Studies in Biological Systems , 2012 .