Pharmacokinetic Problems Research Articles

Time Scale Calculus: a new approach to multi-dose pharmacokinetic modeling

In this paper, we use Time Scale Calculus (TSC) to formulate and solve pharmacokinetic models exploring multiple dose dynamics. TSC is a mathematical framework that allows the modeling of dynamical systems comprising continuous and discrete processes. This characteristic makes TSC particularly suited for multi-dose pharmacokinetic problems, which inherently feature a blend of continuous processes (such as absorption, metabolization, and elimination) and discrete events (drug intake). We use this toolkit to derive analytical expressions for blood concentration trajectories under various multi-dose regimens across several flagship pharmacokinetic models. We demonstrate that this mathematical framework furnishes an alternative and simplified way to model and retrieve analytical solutions for multi-dose dynamics. For instance, it enables the study of blood concentration responses to arbitrary dose regimens and facilitates the characterization of the long-term behavior of the solutions, such as their steady state.

An all-in-one nanoparticle for overcoming drug resistance: doxorubicin and elacridar co-loaded folate receptor targeted PLGA/MSN hybrid nanoparticles

Overexpression of permeability-glycoprotein (P-gp) transporter leads to multidrug resistance (MDR) through cellular exclusion of chemotherapeutics. Co-administration of P-gp inhibitors and chemotherapeutics is a promising approach for improving the efficacy of therapy. Nevertheless, problems in pharmacokinetics, toxicity and solubility limit the application of P-gp inhibitors. Herein, we developed a novel all-in-one hybrid nanoparticle system to overcome MDR in doxorubicin (DOX)-resistant breast cancer. First, folic acid-modified DOX-loaded mesoporous silica nanoparticles (MSNs) were prepared and then loaded into PEGylated poly(lactic-co-glycolic acid) (PLGA) nanoparticles along with a P-gp inhibitor, elacridar. This hybrid nanoparticle system had high drug loading capacity, enabled both passive and active targeting of tumour tissues, and exhibited sequential and pH-triggered release of drugs. In vitro and in vivo studies in DOX-resistant breast cancer demonstrated the ability of the hybrid nanoparticles to reverse P-gp-mediated drug resistance. The nanoparticles were efficiently taken up by the breast cancer cells and delivered elacridar, in vitro. Biodistribution studies demonstrated substantial accumulation of the folate receptor-targeted PLGA/MSN hybrid nanoparticles in tumour-bearing mice. Moreover, deceleration of the tumour growth was remarkable in the animals administered with the DOX and elacridar co-loaded hybrid nanoparticles when compared to those treated with the marketed liposomal DOX (Caelyx®) or its combination with elacridar.

Optimization algorithm of interacting countries and its application for solving problems of pharmacokinetics

With the increasing complexity of optimization problems in the scientific environment, evolutionary algorithms inspired by certain processes in the world are becoming increasingly popular. This paper proposes a new evolutionary algorithm for interacting countries, which is mostly inspired by classical genetic algorithm, island algorithm and migration algorithm. Next, in the article, we study the performance of the algorithm on classical test functions. The results of the algorithm demonstrate its suitability for solving optimization problems and the prospects for its further study. In conclusion, the application of this algorithm to the search for pharmacokinetic constants of the two-compartment model is considered.

Evaluation of prompt engineering strategies for pharmacokinetic data analysis with the ChatGPT large language model.

To systematically assess the ChatGPT large language model on diverse tasks relevant to pharmacokinetic data analysis. ChatGPT was evaluated with prototypical tasks related to report writing, code generation, non-compartmental analysis, and pharmacokinetic word problems. The writing task consisted of writing an introduction for this paper from a draft title. The coding tasks consisted of generating R code for semi-logarithmic graphing of concentration-time profiles and calculating area under the curve and area under the moment curve from time zero to infinity. Pharmacokinetics word problems on single intravenous, extravascular bolus, and multiple dosing were taken from a pharmacokinetics textbook. Chain-of-thought and problem separation were assessed as prompt engineering strategies when errors occurred. ChatGPT showed satisfactory performance on the report writing, code generation tasks and provided accurate information on the principles and methods underlying pharmacokinetic data analysis. However, ChatGPT had high error rates in numerical calculations involving exponential functions. The outputs generated by ChatGPT were not reproducible: the precise content of the output was variable albeit not necessarily erroneous for different instances of the same prompt. Incorporation of prompt engineering strategies reduced but did not eliminate errors in numerical calculations. ChatGPT has the potential to become a powerful productivity tool for writing, knowledge encapsulation, and coding tasks in pharmacokinetic data analysis. The poor accuracy of ChatGPT in numerical calculations require resolution before it can be reliably used for PK and pharmacometrics data analysis.

Deep learning driven de novo drug design based on gastric proton pump structures

Existing drugs often suffer in their effectiveness due to detrimental side effects, low binding affinity or pharmacokinetic problems. This may be overcome by the development of distinct compounds. Here, we exploit the rich structural basis of drug-bound gastric proton pump to develop compounds with strong inhibitory potency, employing a combinatorial approach utilizing deep generative models for de novo drug design with organic synthesis and cryo-EM structural analysis. Candidate compounds that satisfy pharmacophores defined in the drug-bound proton pump structures, were designed in silico utilizing our deep generative models, a workflow termed Deep Quartet. Several candidates were synthesized and screened according to their inhibition potencies in vitro, and their binding poses were in turn identified by cryo-EM. Structures reaching up to 2.10 Å resolution allowed us to evaluate and re-design compound structures, heralding the most potent compound in this study, DQ-18 (N-methyl-4-((2-(benzyloxy)-5-chlorobenzyl)oxy)benzylamine), which shows a Ki value of 47.6 nM. Further high-resolution cryo-EM analysis at 2.08 Å resolution unambiguously determined the DQ-18 binding pose. Our integrated approach offers a framework for structure-based de novo drug development based on the desired pharmacophores within the protein structure.

Conditionally Active, pH-Sensitive Immunoregulatory Antibodies Targeting VISTA and CTLA-4 Lead an Emerging Class of Cancer Therapeutics.

Immune checkpoints and other immunoregulatory targets can be difficult to precisely target due to expression on non-tumor immune cells critical to maintaining immune homeostasis in healthy tissues. On-target/off-tumor binding of therapeutics results in significant pharmacokinetic and pharmacodynamic problems. Target-mediated drug disposition (TMDD) significantly limits effective intratumoral drug levels and adversely affects anti-tumor efficacy. Target engagement outside the tumor environment may lead to severe immune-related adverse events (irAEs), resulting in a narrowing of the therapeutic window, sub-optimal dosing, or cessation of drug development altogether. Overcoming these challenges has become tractable through recent advances in antibody engineering and screening approaches. Here, we review the discovery and development of conditionally active antibodies with minimal binding to target at physiologic pH but high-affinity target binding at the low pH of the tumor microenvironment by focusing on the discovery and improved properties of pH-dependent mAbs targeting two T cell checkpoints, VISTA and CTLA-4.

Discovery of N-(2-oxoethyl) sulfanilamide-derived inhibitors of KAT6A (MOZ) against leukemia by an isostere strategy

KAT6A has been identified as a new target for leukemia treatment. The histone acetyltransferase activity of KAT6A is essential for normal hematopoietic stem cell self-renewal, and mutations or translocations are regarded as one of the major causes of leukemia development. In previous studies, CTX-0124143 has been shown to be a class of KAT6A inhibitors with a sulfonyl hydrazide backbone. However, weak activity, poor selectivity and pharmacokinetic problems have hindered its clinical application. In this work, the N‒N bond in compound CTX-0124143 was replaced by an N-C bond, and the aromatic rings were replaced on both sides. Finally, we obtained Compound 6j. Compared to CTX-0124143, 6j showed a 16-fold stronger inhibition of KAT6A (0.49 μM vs. 0.03 μM) with high selectivity. In addition, 6j exhibited strong antitumor activity on four leukemia cell lines. Moreover, 6j showed significant improvement in metabolic stability and pharmacokinetics in vivo and in vitro. In conclusion, 6j shows excellent potential as a promising anti-leukemia drug candidate.

The discovery of potential tumor necrosis factor alpha converting enzyme inhibitors via implementation of K Nearest Neighbor QSAR analysis

Tumor necrosis factor-alpha converting enzyme (TACE) is considered as a pro-inflammatory cytokine which catalyzes the formation of TNF-α from membrane bound TNF-α precursor protein. It has important role in various pathological diseases such as inflammation, anorexia, rheumatoid arthritis, cancer and viral replication. Despite the reporting of a variety of TACE inhibitors of diverse chemical scaffolds whether peptide, peptide-like compounds or others, the bioavailability and pharmacokinetic problems are reflected strongly on its clinical effectiveness. In this effort we employed a novel combination of k-nearest neighbor QSAR modeling to select the best critical ligand-TACE contacts capable of elucidation of TACE inhibitory bioactivity among a long list of inhibitors. The recurrence of one valid pharmacophore hypothesis among the successful models emerged the pharmacophore to be used as 3D search queries to screen the National Cancer Institute’s structural database for new TACE inhibitors. Eight potent TACE inhibitors were discovered with inhibition percentage exceeding 50% at 100 μM inhibitor concentration.

Resveratrol derivatives: Synthesis and their biological activities

Resveratrol, a natural compound known especially for its antioxidant properties and protective action, opens the door for both it and its structural derivatives to be considered not only as chemopreventive but also as cancer chemotherapeutic agents. Due to the pharmacokinetic problems of resveratrol that demonstrate its poor bioavailability, the study of new derivatives is of interest. Thus, in this work (E)-stilbenes derived directly from resveratrol and other cyclic analogues containing the benzofuran or indole nucleus have been synthesized. The synthesized compounds have been evaluated for their ability to affect tumor growth in vitro. Compounds 2, 3, 4 and 5 have shown cytotoxicity in human colon cancer (HT-29) and human pancreatic adenocarcinoma cells (MIA PaCa-2) higher than those of (E)-resveratrol. The indolic derivative 13, a cyclic analog of resveratrol, has shown in vitro cytotoxic activity 8 times higher than resveratrol against HT-29 cancer cells. The cyclic derivatives 8, 9 and 12 showed a high inhibition of cell growth in HCT-116 (KRas mutant) at 20 μM, while 13 shows moderate antiangiogenesis activity at 10 μM.

Methods for creating a prescribed drug concentration for linear chamber models of pharmacokinetics

One of the main problems of pharmacokinetics is the determination of the therapeutic effect for drugs. With knowledge of the application of numerical methods, it is not difficult to determine the dosing step. In this work, the main techniques for creating a given concentration of drugs are presented. The main theoretical evidence for the creation of specified concentrations is presented. The given evidence is supported by numerical calculations and graphs.

Protac: redirigiendo los sistemas de degradación de proteínas a nuevos sustratos

The small molecules development has dominated the design of new drugs until the rise of nucleic acid-based therapies, either by modifying a gene or by preventing it from being effectively transcribed. Taking advantage of this new approaches, the pharmacological intervention in therapeutic targets that are considered unmodifiable up to now with small molecules were allowed. However, these new approaches are not devoid of defects such as low bioavailability due to their stability and pharmacokinetic problems, in addition to being irreversible DNA modifications in many cases, with the subsequent risk of suffering chronic adverse effects. Alternatively, a series of chimeric heterobifunctional compounds, called PROTACs (Protein Targeting Chimeras), have emerged with force in recent years. These PROTACs are able to bring E3 ligases closer with proteins of interest in space to label them with ubiquitin. Finally, it was degraded by the proteasome. This approach enables the generation of different PROTACs structures by rational design and, also, allows the chemical structure modification to improve their stability and pharmacokinetic profile keeping their activity. This review aims to give a comprehensive approach of what PROTACs are, what E3 ligases recruit, relevant factors in PROTAC development, and other approaches similar to this but that use non-proteasomal degradation pathways.

Succinylated isoniazid potential prodrug: Design of Experiments (DoE) for synthesis optimization and computational study of the reaction mechanism by DFT calculations

Tuberculosis represents a worldwide public health concern, showing high rates of incidence and mortality annually. There is a recommended therapeutic regimen, in which isoniazid is indicated. This drug has a recognized action on Mycobacterium tuberculosis and presents pharmacokinetic problems, which can be improved using prodrug design. Considering that, this paper aimed to apply Design of Experiments (DoE) methods to optimize the synthetic procedure of succinylated isoniazid, a kind of isoniazid prodrug. For this reason, a factorial study 33, varying (1) reaction time (X1) at 6, 12 and 18 h; (2) proportion of excess succinic anhydride (X2) at 1.2, 1.4 and 1.6 equivalents and (3) the different catalysts (X3), pyridine, triethylamine and DMAP were carried out in 19 different experiments (performed in triplicate). It was observed that the condition containing DMAP, 18 h of reaction, presented the best result (85% yield). Additionally, DFT calculations were extremely important for understanding two competitive reaction mechanisms: via a basic DMAP catalysis (Pathway 1) and via self-catalyzed by the succinylated isoniazid (Pathway 2). The presence of a base was fundamental to generate a catalytic amount of product in order to start the Pathway 2. As the reaction goes on and the self-catalyst concentration increases, the Pathway 2 becomes the favorable mechanism, explaining the low influence of the base in the factorial test.

Engineered s-Triazine-Based Dendrimer-Honokiol Conjugates as Targeted MMP-2/9 Inhibitors for Halting Hepatocellular Carcinoma.

Despite the advances in developing MMP-2/9 inhibitors, off-target side effects and pharmacokinetics problems remain major challenges hindering their clinical success in cancer therapy. However, recent targeting strategies have clearly revitalized MMP research. Herein, we introduce new s-triazine-based dendrimers endowed with intrinsic MMP-2/9 inhibitory potential and tetherable to hepatocellular carcinoma-specific targeting ligands and anticancer agents via biodegradable linkages for targeted therapy. The designed dendrimeric platform was built with potential zinc-binding branching linkers (hydrazides) and termini (carboxylic acids and hydrazides) to confer potency against MMP-2/9. Preliminary cytotoxicity screening and MMP-2/9 inhibition assay of the free dendrimers revealed promising potency (MMP-9; IC50 =0.35-0.57 μM, MMP-2; IC50 =0.39-0.77 μM) within their safe doses (EC100 =94.15-42.75 μM). The hydrazide dendrimer was comparable to NNGH and superior to the carboxylic acid analogue. MTT assay showed that the free dendrimers were superior to the reference anticancer agent honokiol. Their anticancer potency was enhanced by HK conjugation, targeting ligands installation and PEGylation as exemplified by the hydrazide dendrimer conjugate (TPG3 -NH2 )-SuHK-FA-SuPEG (Huh-7; IC50 =5.54 μM, HepG-2; IC50 =10.07 μM) being 4 folds more active than HK, followed by the carboxylic acid conjugate (TPG3 -OH)-HK-LA-PEG (Huh-7; IC50 =14.97, HepG-2; IC50 =21.29 μM). This was consistent with apoptosis studies.

Lipid Nanocarriers for Anti-HIV Therapeutics: A Focus on Physicochemical Properties and Biotechnological Advances.

Since HIV was first identified, and in a relatively short period of time, AIDS has become one of the most devastating infectious diseases of the 21st century. Classical antiretroviral therapies were a major step forward in disease treatment options, significantly improving the survival rates of HIV-infected individuals. Even though these therapies have greatly improved HIV clinical outcomes, antiretrovirals (ARV) feature biopharmaceutic and pharmacokinetic problems such as poor aqueous solubility, short half-life, and poor penetration into HIV reservoir sites, which contribute to the suboptimal efficacy of these regimens. To overcome some of these issues, novel nanotechnology-based strategies for ARV delivery towards HIV viral reservoirs have been proposed. The current review is focused on the benefits of using lipid-based nanocarriers for tuning the physicochemical properties of ARV to overcome biological barriers upon administration. Furthermore, a correlation between these properties and the potential therapeutic outcomes has been established. Biotechnological advancements using lipid nanocarriers for RNA interference (RNAi) delivery for the treatment of HIV infections were also discussed.

σ2 Receptor and Its Role in Cancer with Focus on a MultiTarget Directed Ligand (MTDL) Approach.

Sigma-2 (σ2) is an endoplasmic receptor identified as the Endoplasmic Reticulum (ER) transmembrane protein TMEM97. Despite its controversial identity, which was only recently solved, this protein has gained scientific interest because of its role in the proliferative status of cells; many tumor cells from different organs overexpress the σ2 receptor, and many σ2 ligands display cytotoxic actions in (resistant) cancer cells. These properties have shed light on the σ2 receptor as a potential druggable target to be bound/activated for the diagnosis or therapy of tumors. Additionally, diverse groups have shown how the σ2 receptor can be exploited for the targeted delivery of the anticancer drugs to tumors. As the cancer disease is a multifactorial pathology with multiple cell populations, a polypharmacological approach is very often needed. Instead of the simultaneous administration of different classes of drugs, the use of one molecule that interacts with diverse pharmacological targets, namely MultiTarget Directed Ligand (MTDL), is a promising and currently pursued strategy, that may overcome the pharmacokinetic problems associated with the administration of multiple molecules. This review aims to point out the progress regarding the σ2 ligands in the oncology field, with a focus on MTDLs directed towards σ2 receptors as promising weapons against (resistant) cancer diseases.

An Algorithm for Nonparametric Estimation of a Multivariate Mixing Distribution with Applications to Population Pharmacokinetics.

Population pharmacokinetic (PK) modeling has become a cornerstone of drug development and optimal patient dosing. This approach offers great benefits for datasets with sparse sampling, such as in pediatric patients, and can describe between-patient variability. While most current algorithms assume normal or log-normal distributions for PK parameters, we present a mathematically consistent nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions without any assumption about the shape of the distribution. This approach can handle distributions with any shape for all PK parameters. It is shown in convexity theory that the NPML estimator is discrete, meaning that it has finite number of points with nonzero probability. In fact, there are at most N points where N is the number of observed subjects. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. In the simplest case, each point essentially represents the set of PK parameters for one patient. The probability of the points is found by a primal-dual interior-point method; the location of the support points is found by an adaptive grid method. Our method is able to handle high-dimensional and complex multivariate mixture models. An important application is discussed for the problem of population pharmacokinetics and a nontrivial example is treated. Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics. Thereby, this approach presents an important addition to the pharmacometric toolbox for drug development and optimal patient dosing.

Drug-Encapsulated Cyclodextrin Nanosponges.

To date, a number of nanocarriers, either inorganic or organic, have been developed to improve the delivery and therapeutic efficacy of various drugs. Drug delivery systems have attempted to overcome the undesirable pharmacokinetic problems encountered. Among the various nanomaterials that have been designed as potential nanocarriers, cyclodextrin-based polymers are of particular interest in this review.Cyclodextrins (CD) are a class of cyclic glucopyranose oligomers, obtained from starch by enzymatic action, with a characteristic toroidal shape that forms a truncated cone-shaped lipophilic cavity. The main common native cyclodextrins are named α, β, and γ which comprise six, seven, and eight glucopyranose units, respectively. Cyclodextrins have the capability to include compounds whose size and polarity are compatible with those of their cavity.Cyclodextrin-based cross-linked polymers, often referred to as "cyclodextrin nanosponges" (CDNSs), attract great attention from researchers for solving major bioavailability problems such as inadequate solubility, poor dissolution rate, and limited stability of some agents, as well as increasing their effectiveness and decreasing unwanted side effects.Registered patents about this novel system in various fields, different pharmaceutical applications, and classes of drugs encapsulated by CDNSs are detailed. The features outlined make CDNSs a promising platform for the development of innovative and advanced delivery systems.

Development and characterization of thermopressed polyvinyl alcohol films for buccal delivery of benznidazole

Given that oral preparations of benznidazole (BZN) have demonstrated limited efficacy in the treatment of Chagas' disease due to pharmacokinetic or toxicological problems, the development of buccal polymeric films was purposed in this study. These systems ensure high patient acceptability and direct access to the systemic circulation, improving drug bioavailability and toxicological profile. Polymer films were prepared through a thermopressing method by mixing BZN and polyvinyl alcohol (PVAL). In some preparations, propylene glycol (PG) and thymol (TM) were also included as plasticizer and chemical absorption enhancer, respectively. Morphology, X-ray diffraction, spectroscopic, thermal, mechanical, and water uptake properties, as well as ex vivo permeability studies, were performed to characterize the film formulations. BZN remained stable and in an amorphous form over 90 days. The addition of PG and TM improved the mechanical properties of the films, making them soft, flexible and tear-resistant. Also, these additives increased the water sorption rate of the films at 50 and 75% relative humidity and the TM increased the film erosion properties and drug permeability (close to 6×) compared to control. It was hypothesized that the permeability improvement of thymol-based films that follow a drug release profile through erosion is also associated with the inhibition of the crystallization of BNZ when the film is in contact with the buccal mucosa. Once the thymol has previously demonstrated a significant in vivo and in vitro trypanocidal action and even improved film characteristics, these systems may be considered promising for Chagas' disease treatment.

An overview on Pharmacokinetics of Polymeric Nanoparticles Intended for Oral Delivery

Polymeric nanoparticles are investigated as drug delivery devices to overcome physicochemical and pharmacokinetic (PK) problems. Many drugs were found to be drug-like during the pharmacological screening. However, all of them cannot make it to the market due to toxicity and poor bio-availability. The advent of nanoparticles has opened a new window of research where poorly soluble drugs are made useful. Nanoparticles have also been developed for favourable pharmacokinetics to avoid toxicity and side effects, to target the desired site of action and to provide triggered drug release. Poorly soluble drugs can be entrapped, encapsulated, coated or chemically bound in nanoparticles to deliver the drugs. Generally, in standard drug delivery, devices carry the drug until the gastrointestinal tract (GIT) and the drug is released, but the tool never expected to be entering the blood. However, in polymeric nanoparticles, sometimes the drug is being carried to the blood and the site of action. Polymeric nanoparticles release the drug in the gastrointestinal tract (GIT) or enter the GIT through various pathways to appear in the bloodstream. In this review, we discuss the fate of polymeric nanoparticles made up of biodegradable polymers after they are administered through the oral route. Key words: Nanoparticle, Pharmacokinetics, Drug delivery, Polymer, Oral route.

Generalized Optimization of Processes of Drug Transport in Tumors

Optimization and controllability problems for systems described by partial differential equations, where coefficients and the right-hand sides belong to different functional spaces, are considered. In particular, pharmacokinetic problems lead to such models. A model described by a general differential equation with zero initial and boundary conditions is analyzed. Coefficients are assumed positive in this area, concentrated sources are modeled by the Dirac delta function. The search of feasible control that minimizes the quality functional is performed. Based on the space of measurable and square-integrable functions, adjunction for functions smooth in the research area according to the norm, and conjugate problems are constructed. Negative spaces are introduced for the conjugate problem, and generalized solution to the problem is investigated.