Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine

INTRODUCTION

Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hampers accurate prediction of drug candidates' pharmacokinetic properties.

AREAS COVERED

The study highlights current developments in human pharmacokinetic prediction, talks about attempts to apply synthetic approaches for molecular design, and searches several databases, including Scopus, PubMed, Web of Science, and Google Scholar. The article stresses importance of rigorous analysis of machine learning model performance in assessing progress and explores molecular modeling (MM) techniques, descriptors, and mathematical approaches. Transitioning to clinical drug development, article highlights AI (Artificial Intelligence) based computer models optimizing trial design, patient selection, dosing strategies, and biomarker identification. In-silico models, including molecular interactomes and virtual patients, predict drug performance across diverse profiles, underlining the need to align model results with clinical studies for reliability. Specialized training for human specialists in navigating predictive models is deemed critical. Pharmacogenomics, integral to personalized medicine, utilizes predictive modeling to anticipate patient responses, contributing to more efficient healthcare system. Challenges in realizing potential of predictive modeling, including ethical considerations and data privacy concerns, are acknowledged.

EXPERT OPINION

AI models are crucial in drug development, optimizing trials, patient selection, dosing, and biomarker identification and hold promise for streamlining clinical investigations.

Bayesian Optimization-Based Inverse Finite Element Analysis for Atrioventricular Heart Valves

Inverse finite element analysis (iFEA) of the atrioventricular heart valves (AHVs) can provide insights into the in-vivo valvular function, such as in-vivo tissue strains; however, there are several limitations in the current state-of-the-art that iFEA has not been widely employed to predict the in-vivo, patient-specific AHV leaflet mechanical responses. In this exploratory study, we propose the use of Bayesian optimization (BO) to study the AHV functional behaviors in-vivo. We analyzed the efficacy of Bayesian optimization to estimate the isotropic Lee-Sacks material coefficients in three benchmark problems: (i) an inflation test, (ii) a simplified leaflet contact model, and (iii) an idealized AHV model. Then, we applied the developed BO-iFEA framework to predict the leaflet properties for a patient-specific tricuspid valve under a congenital heart defect condition. We found that the BO could accurately construct the objective function surface compared to the one from a [Formula: see text] grid search analysis. Additionally, in all cases the proposed BO-iFEA framework yielded material parameter predictions with average element errors less than 0.02 mm/mm (normalized by the simulation-specific characteristic length). Nonetheless, the solutions were not unique due to the presence of a long-valley minima region in the objective function surfaces. Parameter sets along this valley can yield functionally equivalent outcomes (i.e., closing behavior) and are typically observed in the inverse analysis or parameter estimation for the nonlinear mechanical responses of the AHV. In this study, our key contributions include: (i) a first-of-its-kind demonstration of the BO method used for the AHV iFEA; and (ii) the evaluation of a candidate AHV in-silico modeling approach wherein the chordae could be substituted with equivalent displacement boundary conditions, rendering the better iFEA convergence and a smoother objective surface.

An image-driven micromechanical approach to characterize multiscale remodeling in infarcted myocardium

Myocardial infarction (MI) is accompanied by the formation of a fibrotic scar in the left ventricle (LV) and initiates significant alterations in the architecture and constituents of the LV free wall (LVFW). Previous studies have shown that LV adaptation is highly individual, indicating that the identification of remodeling mechanisms post-MI demands a fully subject-specific approach that can integrate a host of structural alterations at the fiber-level to changes in bulk biomechanical adaptation at the tissue-level. We present an image-driven micromechanical approach to characterize remodeling, assimilating new biaxial mechanical data, histological studies, and digital image correlation data within an in-silico framework to elucidate the fiber-level remodeling mechanisms that drive tissue-level adaptation for each subject. We found that a progressively diffused collagen fiber structure combined with similarly disorganized myofiber architecture in the healthy region leads to the loss of LVFW anisotropy post-MI, offering an important tissue-level hallmark for LV maladaptation. In contrast, our results suggest that reductions in collagen undulation are an adaptive mechanism competing against LVFW thinning. Additionally, we show that the inclusion of subject-specific geometry when modeling myocardial tissue is essential for accurate prediction of tissue kinematics. Our approach serves as an essential step toward identifying fiber-level remodeling indices that govern the transition of MI to systolic heart failure. These indices complement the traditional, organ-level measures of LV anatomy and function that often fall short of early prognostication of heart failure in MI. In addition, our approach offers an integrated methodology to advance the design of personalized interventions, such as hydrogel injection, to reinforce and suppress native adaptive and maladaptive mechanisms, respectively, to prevent the transition of MI to heart failure. STATEMENT OF SIGNIFICANCE: Biomechanical and architectural adaptation of the LVFW remains a central, yet overlooked, remodeling process post-MI. Our study indicates the biomechanical adaptation of the LVFW post-MI is highly individual and driven by altered fiber network architecture and collective changes in collagen fiber content, undulation, and stiffness. Our findings demonstrate the possibility of using cardiac strains to infer such fiber-level remodeling events through in-silico modeling, paving the way for in-vivo characterization of multiscale biomechanical indices in humans. Such indices will complement the traditional, organ-level measures of LV anatomy and function that often fall short of early prognostication of heart failure in MI.

The rise of the sourdough: Genome-scale metabolic modeling-based approach to design sourdough starter communities with tailored-made properties

Sourdough starters harbor microbial consortia that benefit the final product's aroma and volume. The complex nature of these spontaneously developed communities raises challenges in predicting the fermentation phenotypes. Herein, we demonstrated for the first time in this field the potential of genome-scale metabolic modeling (GEMs) in the study of sourdough microbial communities. Broad in-silico modeling of microbial growth was applied on communities composed of yeast (Saccharomyces cerevisiae) and different Lactic Acid Bacteria (LAB) species, which mainly predominate in sourdough starters. Simulations of model-represented communities associated specific bacterial compositions with sourdough phenotypes. Based on ranking the phenotypic performances of different combinations, Pediococcus spp. - Lb. sakei group members were predicted to have an optimal effect considering the increase in S. cerevisiae growth abilities and overall CO2 secretion rates. Flux Balance Analysis (FBA) revealed mutual relationships between the Pediococcus spp. - Lb. sakei group members and S. cerevisiae through bidirectional nutrient dependencies, and further underlined that these bacteria compete with the yeast over nutrients to a lesser extent than the rest LAB species. Volatile compounds (VOCs) production was further modeled, identifying species-specific and community-related VOCs production profiles. The in-silico models' predictions were validated by experimentally building synthetic sourdough communities and assessing the fermentation phenotypes. The Pediococcus spp. - Lb. sakei group was indeed associated with increased yeast cell counts and fermentation rates, demonstrating a 25 % increase in the average leavening rates during the first 10 fermentation hours compared to communities with a lower representation of these group members. Overall, these results provide a possible novel strategy towards the de-novo design of sourdough starter communities with tailored-made characterizations, including a shortened leavening period.

Fabrication, in-silico, in-vitro, and in-vivo characterization of transferrin-targeted micelles containing cisplatin and gadolinium for improved theranostic applications in lung cancer therapy

The targeted delivery of therapeutic and imaging agents is quite challenging in lung cancer therapy. Thus, lung cancer causes high mortality across the world. Herein, we developed TPGS-PF127 micelles containing cisplatin (CDDP) as a model anticancer drug and gadolinium (Gd) as a diagnostic agent by a slightly modified solvent casting method, further, the surface of the micelles was modified using TPGS-transferrin (TPGS-Tf) conjugate to improve targeted delivery of micelles to the lung cancer cells. Prior to this, the binding affinity of Tf over TfR (1E7U) and TfR (1E8W) was investigated with the help of in-silico studies. In-silico results showed good docking scores -7.8 and -7.2 kcal/mol of Tf -ligand towards 1E8W and 1E7U respectively promoting PI3K inhibition. Micelles have shown an average particle size range of 80-200 nm and have shown spherical morphology. The encapsulation efficiency of cisplatin (CDDP) in the CPT, CGPT, and CGPT-Tf micelles ranged from 75.63 % ± 1.58 % to 85.07 % ± 2.65 %. Furthermore, the encapsulation efficiency of gadolinium (Gd) in the CGPT and CGPT-Tf micelles was found to be 67.50 ± 0.32 % and 62.52 ± 0.52 %, respectively. CGPT-Tf micelles exhibited sustained release fashion for CDDP up to 48 h in physiological conditions. In the cytotoxicity study, CGPT-Tf micelles achieved higher cytotoxicity and caused a more antiproliferative effect in A549 cells compared to a commercial CDDP injection (Ciszest 50), after 24 h of treatment. Furthermore, the pharmacokinetic studies have proven the pharmacological effectiveness of developed CGPT-Tf micelles by achieving higher Cmax, Tmax, t1/2, and MRT of CDDP in systemic circulation compared to its counterparts and Ciszest 50. In lung theranostic observations, a higher internalization of Gd was noted in CGPT-TF compared to free Gd. The biochemical studies have proved the biocompatibility of developed micelles formulations by showing no sign of toxicity in the lungs. The developed micelles have great potential to be utilized in treating and diagnosing a wide variety of cancers.

Effect of artificial surface shapes and their malpositioning on the mechanics of the replaced ankle joint for possible better prosthesis designs

BACKGROUND

The clinical outcomes of total ankle replacement are limited by prosthesis component malpositioning during surgery. The goal of this study is to assess the mechanical impact of this malpositioning in a validated computer model.

METHODS

In a previously developed multi-body dynamic model of the human ankle complex three different artificial implants were designed, each one presenting a different approximation of the natural articular surfaces of the corresponding specimen. The most common implant translational and rotational malpositionings were defined and mimicked. Dynamic simulations of joint motion were run for the various surfaces and malpositionings. The same input loading conditions derived from a previous in-vitro experiment on the corresponding natural specimen were applied.

FINDINGS

From load-displacement graphs it was observed that all three artificial surfaces reproduced well physiological motion between the calcaneus and the tibia/fibula, with a maximum difference of 2°. It was found that antero-posterior translation of either the tibial or the talar component and inclination of the tibial component in the sagittal plane led to considerable increases in the range of motion. Antero-posterior and dorsiflexion of the tibial component resulted in an increased internal-external rotation by up to 3.5° and 4.0°, respectively. The corresponding increase of inversion-eversion was 5.0° and 6.5°.

INTERPRETATION

This study showed that relatively small surgical errors have great consequences in replaced joint mechanics. The present model can be used in future studies to analyse the effect of malpositioning with any specific current total ankle prosthesis.

Isolation and characterization of thermal degradation impurity in brimonidine tartrate by HPLC, LC-MS/MS, and 2DNMR

One potential unknown impurity was detected during the analysis of stability batches of brimonidine tartrate (BMT) in the level ranging from 0.03 % to 0.06 % by high-performance liquid chromatography (HPLC). Based on the liquid chromatography-mass spectrophotometry (LC-MS) analysis, the unknown impurity structure was presumed as 3,6,11,13,16-pentaazatetracyclo [8.6.0.0²,⁷.0¹²,¹⁶] hexadeca-1,3,5,7,9,12-hexaene. The proposed structure was elucidated, after its isolation using preparative liquid chromatography from the impurity enriched reaction crude sample, using analytical applications such as 1D NMR (¹H, ¹³C and DEPT-135), 2D NMR (HMBC and COSY), high-resolution mass spectrometry (HRMS) and infrared spectroscopy (IR). The unknown impurity was prepared from brimonidine by following Ullman coupling reaction in the presence of CuBr₂ in gram scale with optimum purity to use further in analytical developments. The identification, structural elucidation and synthesis of unknown degradation impurity such as BMT-cyclized impurity, and HPLC method validation were reported for the first time in this paper.

Analytical methods for braided stents design and comparison with FEA

Braiding technology is nowadays commonly adopted to build stent-like devices. Indeed, these endoprostheses, thanks to their typical great flexibility and kinking resistance, find several applications in mini-invasive treatments, involving but not limiting to the cardiovascular field. The design process usually involves many efforts and long trial and error processes before identifying the best combination of manufacturing parameters. This paper aims to provide analytical tools to support the design and optimization phases: the developed equations, based on few geometrical parameters commonly used for describing braided stents and material stiffness, are easily implementable in a worksheet and allow predicting the radial rigidity of braided stents, also involving complex features such as multiple twists and looped ends, and the diameter variation range. Finite element simulations, previously validated with respect to experimental tests, were used as a comparator to prove the reliability of the analytical results. The illustrated tools can assess the impact of each selected parameter modification and are intended to guide the optimal selection of geometrical and mechanical stent proprieties to obtain the desired radial rigidity, deliverability (minimum diameter), and, if forming processes are planned to modify the shape of the stent, the required diameter variations (maximum and minimum diameters).

Hydrophobic functionalization reactions of structured cellulose nanomaterials: Mechanisms, kinetics and in silico multi-scale models

Nanoscale-interfaced cellulose nanomaterials are extracted from polysaccharides, which are widely available in nature, biocompatible and biodegradable. Moreover, the latter have a potential to be recycled, upcycled, and formulate therefore a great theoretical predisposition to be used in a number of applications. Nanocrystals, nano-fibrils and nanofibers possess reactive functional groups that enable hydrophobic surface modifications. Analysed literature data, concerning mechanisms, pathways and kinetics, was screened, compared and assessed with regard to the demand of a catalyst, different measurement conditions and added molecule reactions. There is presently only a scarce technique description for carbonOH bond functionalization, considering the elementary chemical steps, sequences and intermediates of these (non)catalytic transformations. The overview of the prevailing basic research together with in silico modelling approach methodology gives us a deeper physical understanding of processes. Finally, to further highlight the applicability of such raw materials, the review of the development in several multidisciplinary fields was presented.

Finite Element Simulations of the ID Venous System to Treat Venous Compression Disorders: From Model Validation to Realistic Implant Prediction

The ID Venous System is an innovative device proposed by ID NEST MEDICAL to treat venous compression disorders that involve bifurcations, such as the May-Thurner syndrome. The system consists of two components, ID Cav and ID Branch, combined through a specific connection that prevents the migration acting locally on the pathological region, thereby preserving the surrounding healthy tissues. Preliminary trials are required to ensure the safety and efficacy of the device, including numerical simulations. In-silico models are intended to corroborate experimental data, providing additional local information not acquirable by other means. The present work outlines the finite element model implementation and illustrates a sequential validation process, involving seven tests of increasing complexity to assess the impact of each numerical uncertainty separately. Following the standard ASME V&V40, the computational results were compared with experimental data in terms of force-displacement curves and deformed configurations, testing the model reliability for the intended context of use (differences < 10%). The deployment in a realistic geometry confirmed the feasibility of the implant procedure, without risk of rupture or plasticity of the components, highlighting the potential of the present technology.

"Pelargonidin mediated selective activation of p53 and parp proteins in preventing food additive induced genotoxicity: an in vivo coupled in silico molecular docking study"

Food-additive toxicity has become a major health hazard issue globally. Alloxan (ALX), a food-additive, intaken daily through flour causes diabetes and genotoxicity by inducing chromosomal-aberration and DNA-damage. The use of phytochemicals as a protective measure of health hazards has become quite evident because of their least side effects. Pelargonidin (PG), one such phyto-product, have an anti-genotoxic and anti-diabetic effect. In this study, the possibility of PG to inhibit alloxan-induced chromosomal-aberration and DNA-damage was assessed in mice model in vivo and the experimental outcome was validated theoretically through in silico structure-based molecular docking study. Results of the mitotic-index observed from the PG-pre-treated-alloxan-administered (PG+ALX) mice group revealed a significant reduction in chromosomal-anomaly, DNA-damage, and an upregulation of the p53 and PARP protein expression when compared to the ALX-treated mice group. Additionally, the in silico molecular docking study predicted the biochemical mechanism of actions of pelargonidin by identifying the two important amino acid residues p53 and PARP as the active bio-targets of pelargonidin. Therefore, results of our present in vivo and silico studies implicate that pelargonidin could effectively restrict DNA-damage and chromosomal-aberration by modulating PARP and p53 repair proteins showing its ability for possible protein-drug interaction, an effective therapeutic tool in future drug discovery.

Chromatography bioseparation technologies and in-silico modelings for continuous production of biotherapeutics

The potential of continuous bioprocessing is hindered by the bottlenecks of chromatography processing, which continues to be executed in batch mode. Highlighting the critical drawbacks of batch chromatography, this review underscores the transition that the industry has made by implementing continuous upstream process without devising a working model for downstream chromatography operations. Even though multitude of process development initiatives have commenced, the review emphasizes the first principle models of chromatography on which these initiatives are built. Various models of continuous chromatography, which are essential, but not limited to multi-column systems, employed to congeal a unified process are reviewed. Advancements made by several mechanistic models and simulations to maximize productivity and performance are described, in an attempt to provide the integral tools. The modeling tools can be used for development of a strong model based control strategy and can be embedded into the continuous chromatography framework. The review addresses the limitations and challenges of the current modeling methods for development of robust mechanistic modeling and efficient unit operation platform in continuous chromatography.

Proteomic analysis of JAZ interacting proteins under methyl jasmonate treatment in finger millet

Jasmonic acid (JA) signaling pathway in plants is activated against various developmental processes as well as biotic and abiotic stresses. The Jasmonate ZIM-domain (JAZ) protein family, the key regulator of plant JA signaling pathway, also participates in phytohormone crosstalk. This is the first study revealing the in vivo interactions of finger millet (Eleusine coracana (L.) Gaertn.) JAZ protein (EcJAZ) under methyl jasmonate (MJ) treatment. The aim of the study was to explore not only the JA signaling pathway but also the phytohormone signaling crosstalk of finger millet, a highly important future crop. From the MJ-treated finger millet seedlings, the EcJAZ interacting proteins were purified by affinity chromatography with the EcJAZ-matrix. Twenty-one proteins of varying functionalities were successfully identified by MALDI-TOF-TOF Mass spectrometry. Apart from the previously identified JAZ binding proteins, most prominently, EcJAZ was found to interact with transcription factors like NAC, GATA and also with Cold responsive protein (COR), etc. that might have extended the range of functionalities of JAZ proteins. Moreover, to evaluate the interactions of EcJAZ in the JA-co-receptor complex, we generated ten in-silico models containing the EcJAZ degron and the COI1-SKP1 of five monocot cereals viz., rice, wheat, maize, Sorghum and Setaria with JA-Ile or coronatine. Our results indicated that the EcJAZ protein of finger millet could act as the signaling hub for the JA and other phytohormone signaling pathways, in response to a diverse set of stressors and developmental cues to provide survival fitness to the plant.