A multi-scale stochastic drug release model for polymer-coated targeted drug delivery systems

Integration of advanced methods and models to study drug absorption and related processes: An UNGAP perspective

This collection of contributions from the European Network on Understanding Gastrointestinal Absorption-related Processes (UNGAP) community assembly aims to provide information on some of the current and newer methods employed to study the behaviour of medicines. It is the product of interactions in the immediate pre-Covid period when UNGAP members were able to meet and set up workshops and to discuss progress across the disciplines. UNGAP activities are divided into work packages that cover special treatment populations, absorption processes in different regions of the gut, the development of advanced formulations and the integration of food and pharmaceutical scientists in the food-drug interface. This involves both new and established technical approaches in which we have attempted to define best practice and highlight areas where further research is needed. Over the last months we have been able to reflect on some of the key innovative approaches which we were tasked with mapping, including theoretical, in silico, in vitro, in vivo and ex vivo, preclinical and clinical approaches. This is the product of some of us in a snapshot of where UNGAP has travelled and what aspects of innovative technologies are important. It is not a comprehensive review of all methods used in research to study drug dissolution and absorption, but provides an ample panorama of current and advanced methods generally and potentially useful in this area. This collection starts from a consideration of advances in a priori approaches: an understanding of the molecular properties of the compound to predict biological characteristics relevant to absorption. The next four sections discuss a major activity in the UNGAP initiative, the pursuit of more representative conditions to study lumenal dissolution of drug formulations developed independently by academic teams. They are important because they illustrate examples of in vitro simulation systems that have begun to provide a useful understanding of formulation behaviour in the upper GI tract for industry. The Leuven team highlights the importance of the physiology of the digestive tract, as they describe the relevance of gastric and intestinal fluids on the behaviour of drugs along the tract. This provides the introduction to microdosing as an early tool to study drug disposition. Microdosing in oncology is starting to use gamma-emitting tracers, which provides a link through SPECT to the next section on nuclear medicine. The last two papers link the modelling approaches used by the pharmaceutical industry, in silico to Pop-PK linking to Darwich and Aarons, who provide discussion on pharmacometric modelling, completing the loop of molecule to man.

Preparation, characterization, drug release and computational modelling studies of antibiotics loaded amorphous chitin nanoparticles

We present a computational investigation of binding affinity of different types of drugs with chitin nanocarriers. Understanding the chitn polymer-drug interaction is important to design and optimize the chitin based drug delivery systems. The binding affinity of three different types of anti-bacterial drugs Ethionamide (ETA) Methacycline (MET) and Rifampicin (RIF) with amorphous chitin nanoparticles (AC-NPs) were studied by integrating computational and experimental techniques. The binding energies (BE) of hydrophobic ETA, hydrophilic MET and hydrophobic RIF were -7.3kcal/mol, -5.1kcal/mol and -8.1kcal/mol respectively, with respect to AC-NPs, using molecular docking studies. This theoretical result was in good correlation with the experimental studies of AC-drug loading and drug entrapment efficiencies of MET (3.5±0.1 and 25± 2%), ETA (5.6±0.02 and 45±4%) and RIF (8.9±0.20 and 53±5%) drugs respectively. Stability studies of the drug encapsulated nanoparticles showed stable values of size, zeta and polydispersity index at 6°C temperature. The correlation between computational BE and experimental drug entrapment efficiencies of RIF, ETA and MET drugs with four AC-NPs strands were 0.999 respectively, while that of the drug loading efficiencies were 0.854 respectively. Further, the molecular docking results predict the atomic level details derived from the electrostatic, hydrogen bonding and hydrophobic interactions of the drug and nanoparticle for its encapsulation and loading in the chitin-based host-guest nanosystems. The present results thus revealed the drug loading and drug delivery insights and has the potential of reducing the time and cost of processing new antibiotic drug delivery nanosystem optimization, development and discovery.

In-line spatial filtering velocimetry for particle size and film thickness determination in fluidized-bed pellet coating processes

A spatial filtering velocimetry (SFV) probe was applied to monitor the increase in particle size during pellet Wurster coating processes in-line. Accuracy of the in-line obtained pellet sizes was proven by at-line performed digital image analysis (DIA). Regarding particle growth, high conformity between both analytical methods (SFV/DIA) was examined for different coating processes. The influence of ring buffer size and the process of filling the buffer were investigated. With buffer sizes of 30,000-50,000 particles best results were obtained in this study. Investigated process parameters, such as inlet air volume and spray rate, had different effects on the impact of the SFV probe. While the particle rate (the number of particles detected by the SVF probe per second) was highly dependent on the inlet air volume, different spray rates of up to ・}1 g/min did not affect the detected particle growth. Artefacts and delays in SFV particle sizing appeared especially at the beginning of the coating processes. The slope of the particle growth during the final spraying period was therefore used to determine coating thickness.

Molecular dynamics simulation of drug uptake by polymer

Drug uptake by polymer was modeled using a molecular dynamics (MD) simulation technique. Three drugs--doxorubicin (water soluble), silymarin (sparingly water soluble) and gliclazide (water insoluble)--and six polymers with varied functional groups--alginic acid, sodium alginate, chitosan, Gantrez AN119 (methyl-vinyl-ether-co-malic acid based), Eudragit L100 and Eudragit RSPO (both acrylic acid based)--were selected for the study. The structures were modeled and minimized using molecular mechanics force field (MM+). MD simulation (Gromacs-forcefield, 300 ps, 300 K) of the drug in the vicinity of the polymer molecule in the presence of water molecules was performed, and the interaction energy (IE) between them was calculated. This energy was evaluated with respect to electric-dipole, van der Waals and hydrogen bond forces. A good linear correlation was observed between IE and our own previous data on drug uptake(*) [R² = 0.65, R²adj = 0:65; R²pre = 0:56 and a F ratio of 30.25, P < 0.001; Devarajan et al. (2005) J Biomed Nanotechnol 1:1-9]. Maximum drug uptake by the polymeric nanoparticles (NP) was achieved in water as the solvent environment. Hydrophilic interaction between NP and water was inversely correlated with drug uptake. The MD simulation method provides a reasonable approximation of drug uptake that will be useful in developing polymer-based drug delivery systems.

Polymer-drug interactions in tyrosine-derived triblock copolymer nanospheres: a computational modeling approach

A combination of molecular dynamics (MD) simulations and docking calculations was employed to model and predict polymer-drug interactions in self-assembled nanoparticles consisting of ABA-type triblock copolymers, where A-blocks are poly(ethylene glycol) units and B-blocks are low molecular weight tyrosine-derived polyarylates. This new computational approach was tested on three representative model compounds: nutraceutical curcumin, anticancer drug paclitaxel and prehormone vitamin D3. Based on this methodology, the calculated binding energies of polymer-drug complexes can be correlated with maximum drug loading determined experimentally. Furthermore, the modeling results provide an enhanced understanding of polymer-drug interactions, revealing subtle structural features that can significantly affect the effectiveness of drug loading (as demonstrated for a fourth tested compound, anticancer drug camptothecin). The present study suggests that computational calculations of polymer-drug pairs hold the potential of becoming a powerful prescreening tool in the process of discovery, development and optimization of new drug delivery systems, reducing both the time and the cost of the process.

SIMDOT-AbMe: microphysiologically based simulation tool for quantitative prediction of systemic and local bioavailability of targeted oral delivery formulations

The purpose of this study was to develop a physiologically based simulation tool that is able to predict local as well as systemic bioavailability of 5-aminosalicylic acid (5-ASA)-targeted delivery formulations using the existing understanding of the transport and metabolism mechanisms of 5-ASA. The model accounts for active and passive transcellular transport (absorptive and efflux), passive paracellular transport, intestinal biotransformation, and systemic metabolism and clearance. The intestinal physiology was represented by transverse segments for ileum and proximal colon and longitudinal compartments for the microphysiology of the intestinal tissue. The tool, equipped with an optimization routine that enables tuning model parameters, was developed in Matlab and uses a user-friendly graphical interface for data input and output. Physiologic and kinetic model parameters were estimated either from literature monolayer transport studies using nonlinear curve fitting or obtained directly from the literature. 5-ASA clinical pharmacokinetic profiles of a once-daily (one 4-g/day dose) and twice-daily (two 2-g/day doses) dosing regimen were used to partially calibrate and validate the model, respectively. Simulation results showed that drug C(max) in the gut mucosal layers reached a higher level and was achieved sooner than in the systemic blood level. The computed relative local bioavailability with respect to the systemic bioavailability was 0.063. With use of the model, the relative local bioavailability of different formulations can be established for fast performance verification of new preparations based on measured systemic bioavailability. These types of models play a critical role in designing such preparations and rapidly assessing their effectiveness and will foster efficient experimental designs, saving time and resources.

Modeling doxorubicin transport to improve intratumoral drug delivery to RF ablated tumors

A mathematical model of drug transport provides an ideal strategy to optimize intratumoral drug delivery implants to supplement radiofrequency (RF) ablation for tumor treatment. To simulate doxorubicin transport in non-ablated and ablated liver tumors, a one-dimensional, cylindrically symmetric transport model was generated using a finite element method (FEM). Parameters of this model, the diffusion (D) and elimination (gamma) coefficients for doxorubicin, were estimated using drug distributions measured 4 and 8 days after placing biodegradable implants in non-ablated and ablated rabbit VX2 liver carcinomas. In non-ablated tumor, values of diffusion and elimination parameters were 25% and 94% lower than normal liver tissue, respectively. In ablated tumor, diffusion near the ablation center was 75% higher than non-ablated tumor but decreased to the non-ablated tumor value at the ablation periphery. Drug elimination in ablated tumor was zero for the first four days, but by day 8 returned to 98% of the value for non-ablated tumor. Three-dimensional (3-D) simulations of drug delivery from implants with and without RF thermal ablation underscore the benefit of using RF ablation to facilitate local drug distribution. This study demonstrates the use of computational modeling and optimal parameter estimation to predict local drug pharmacokinetics from intratumoral implants after ablation.

Binary polymeric blends to microencapsulate nitroflurbiprofen: Physicochemical and in silico studies

Nitroflurbiprofen, NFP, a practically insoluble liquid drug, was microencapsulated in hydrophilic micromatrices made of poly(N-vinylpyrrolidone) (PVP), or polyaminomethacrylate (PAMA), or binary blends of polymers thereof. The PAMA/PVP miscibility was assessed both in the solid state (DSC and ATF-FTIR spectroscopy) and in solution by viscometric measurements. The in vitro NFP release test was carried out in over saturation condition to discriminate the increase of NFP apparent solubility (supersaturation degree, SD). Drug/polymer/polymer/water interactions were studied in silico by molecular dynamic (MD) simulations. PAMA and PVP resulted miscible only in aqueous solution. The release of NFP from microparticles occurred according to a non-monotonic pattern due to the formation of instable supersaturated systems and the drug separation in the dissolution medium. After 5 min, the SD was at least 3. The use of PVP/PAMA micromatrices reduced the instability of the supersaturated solutions. MD simulations evidenced that water molecules play a key role in the PAMA/PVP compatibilization process and in stabilization of NFP supersaturated systems by means of H-bond. The docking analyses here find a novel and successful application to predict the different ability of a drug to interact with polymeric blends in solution.

Advanced pharmacokinetic models based on organ clearance, circulatory, and fractal concepts

Three advanced models of pharmacokinetics are described. In the first class are physiologically based pharmacokinetic models based on in vitro data on transport and metabolism. The information is translated as transporter and enzyme activities and their attendant heterogeneities into liver and intestine models. Second are circulatory models based on transit time distribution and plasma concentration time curves. The third are fractal models for nonhomogeneous systems and non-Fickian processes are presented. The usefulness of these pharmacokinetic models, with examples, is compared.