Tackling pharmacological response heterogeneity by PBPK modeling to advance precision medicine productivity of nanotechnology and genomics therapeutics

ABSTRACT

Introduction: Nowadays, nanotechnology and genomics contribute knowledge and innovative practices, enabling pharmacological interventions as well as theraputic decisions to be applicable on a personal basis, i.e., establishing precision (personalized) medicine approaches into the clinical setting. However, the dynamics and the evolution capacity of organisms over time necessitate the advancement of powerful interdisciplinary tools, population-based pharmacological methodologies, as well as the application of translational methodologies with clinical implementation capabilities.

Areas covered: Even for newly emerged techniques, like three-dimensional (3D) bioprinting nanoplatforms and in vitro transcribed (IVT)-mRNA therapeutics, the patients’ heterogeneity still hinders their potential exploitation in a broader perspective and clinical outcome burden. It is thus essential that the recently developed computational physiologically-based pharmacokinetic (PBPK) models present tools aiming to predict differential pharmacological response in patient groups and to allow cost-effective individualized dosage adjustments for populations worldwide.

Expert opinion: The recent advancements in IVT-mRNA therapeutics and 3D bioprinting technologies, along with the capabilities of PBPK modeling to delineate the issue of interpatient heterogeneity, will be presented and discussed. Also, the integration of core interdisciplinary infrastructures will be included in a manner to better serve the task of more efficiently and productively achieving precision medicine interventions in the everyday clinical practice.

KEYWORDS:

• Precision medicine
• PBPK modeling
• innovative therapeutics

Article highlights

• The molecular heterogeneity modulates the pharmacological response variability thus leading to limited productivity and market approval of innovative therapeutics developments.

• PBPK modeling represents a powerful tool to predict differential pharmacological response variability in different patient populations.

• The bioinformatics pipeline infrastructures keep the translational capacity for the clinical implementation of -OMICs knowledge in routine healthcare globally.

• PBPK integrative modeling has been developed and entered drug regulatory body guidelines by allowing multifactor correlation analysis from diverse panels of drug-related data.

• Big data analytics and machine learning methodologies present the needed power in real-time to delineate molecular diversity of clinical relevance and utility.

• The generation of a dual PBPK/bioinformatic ‘pan-simulation’ avatar model for individual patients could guide personalized-based therapeutic decisions in the clinical setting.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

AN Miliotou has been financially supported by General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI) (Scholarship Code: 1533).