Modeling bioavailability to organs protected by biological barriers

Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products

Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).

Physiologically Based Pharmacokinetic Modeling of Nanoparticles

Nanoparticles are frequently designed to improve the pharmacokinetics profiles and tissue distribution of small molecules to prolong their systemic circulation, target specific tissue, or widen the therapeutic window. The multifunctionality of nanoparticles is frequently presented as an advantage but also results in distinct and complicated in vivo disposition properties compared with a conventional formulation of the same molecules. Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool in characterizing and predicting the systemic disposition, target exposure, and efficacy and toxicity of various types of drugs when coupled with pharmacodynamic modeling. Here we review the unique disposition characteristics of nanoparticles, assess how PBPK modeling takes into account the unique disposition properties of nanoparticles, and comment on the applications and challenges of PBPK modeling in characterizing and predicting the disposition and biological effects of nanoparticles.

Different expression of β subunits of the KCa1.1 channel by invasive and non-invasive human fibroblast-like synoviocytes

Background

Fibroblast-like synoviocytes (FLS) in rheumatoid arthritis (RA-FLS) contribute to joint inflammation and damage characteristic of the disease. RA-FLS express KCa1.1 (BK, Slo1, MaxiK, KCNMA1) as their major plasma membrane potassium channel. Blocking KCa1.1 reduces the invasive phenotype of RA-FLS and attenuates disease severity in animal models of RA. This channel has therefore emerged as a promising therapeutic target in RA. However, the pore-forming α subunit of KCa1.1 is widely distributed in the body, and blocking it induces severe side effects, thus limiting its value as a therapeutic target. On the other hand, KCa1.1 channels can also contain different accessory subunits with restricted tissue distribution that regulate channel kinetics and pharmacology. Identification of the regulatory subunits of KCa1.1 expressed by RA-FLS may therefore provide the opportunity for generating a selective target for RA treatment.

Methods

Highly invasive RA-FLS were isolated from patients with RA, and FLS from patients with osteoarthritis (OA) were used as minimally invasive controls. The β subunit expression by FLS was assessed by quantitative reverse transcription polymerase chain reactions, Western blotting, and patch-clamp electrophysiology combined with pharmacological agents. FLS were sorted by flow cytometry on the basis of their CD44 expression level for comparison of their invasiveness and with their expression of KCa1.1 α and β subunits. β1 and β3 subunit expression was reduced with small interfering RNA (siRNA) to assess their specific role in KCa1.1α expression and function and in FLS invasiveness.

Results

We identified functional β1 and β3b regulatory subunits in RA-FLS. KCa1.1 β3b subunits were expressed by 70 % of the cells and were associated with highly invasive CD44^high RA-FLS, whereas minimally invasive CD44^low RA-FLS and OA-FLS expressed either β1 subunit. Furthermore, we found that silencing the β3 but not the β1 subunit with siRNA reduced KCa1.1 channel density at the plasma membrane of RA-FLS and inhibited RA-FLS invasiveness.

Conclusions

Our findings suggest the KCa1.1 channel composed of α and β3b subunits as an attractive target for the therapy of RA.

Computational pharmacokinetics at a crossroads

This first special issue of In Silico Pharmacology focuses on computational pharmacokinetics since they are an important part of integrated applications in computational pharmacology. The important topics of model structure, model parameterization, improved organ description, and modeling of drug-drug interactions are covered. They are actually at the crossroads between several emerging disciplines which will shape the future of therapeutic treatments and public health.