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Biological cascade of BRAFV600E activation and cell cycle implications. The BRAFV600E pathway includes multiple biomarkers whose direct or indirect response could be indicative of efficacy.
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Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs in the pharmaceutical industry. The purpose of this publication is to serve as a guide for drug discovery scientists toward optimal design and conduct...
Citations
... Our assessment focused predominantly on maternal and embryo-fetal toxicity, alongside selected biochemical markers of liver and kidney function, omitting comprehensive evaluations of other critical aspects such as neurotoxicity, immunotoxicity, or carcinogenic potential [33], as performed for other potentially harmful molecules [34,35]. Moreover, the study did not delve into the pharmacokinetics and pharmacodynamics of piplartine, factors essential for understanding its systemic behavior, optimizing dosing, and foreseeing drug-drug interactions [36,37]. Similarly, assessments of bioavailability and biodistribution were absent, crucial for evaluating efficacy and safety, especially concerning target tissue reach and effect [38,39]. ...
Piplartine, also known as piperlongumine, is a natural and biologically active amide alkaloid found in various Piper species within the Piperaceae family. It possesses numerous beneficial properties that can be leveraged in the development of nanotechnological and pharmaceutical products. However, information on the effects of piplartine on mammalian embryonic development is scarce. This study aims to assess the general toxicity and teratogenic potential of piplartine during the embryonic development of mice. Pregnant mice received daily treatments of 25, 50, or 100 mg/kg of piplartine via gavage from the sixth day of gestation (implantation) to the eighteenth. On the eighteenth day, the mice were euthanized, and whole organs, blood samples (for hematological and biochemical analyses), and bone marrow cells (for DNA fragmentation and cell cycle assays) were collected. The uterus was examined for implantation sites and embryo resorptions. Additionally, fetuses were collected to assess for fetal anomalies. Piplartine did not result in maternal or embryo-fetal toxicity, induce fetal anomalies, cause hematological and biochemical alterations, or lead to DNA fragmentation. The oral administration of piplartine is safe and does not exhibit toxicity or teratogenic effects in mice. This finding opens avenues for the development of piplartine-based biotechnological products for therapeutic interventions in disease treatment.
... Recent regulatory guidance has acknowledged the free drug hypothesis and recommended the use of unbound drug concentrations in potential DDI liability estimations for cytochrome P450 and transporter proteins inhibition and/or induction studies (Cole et al., 2020;Sudsakorn et al., 2020;ICH, 2022). Similarly, the free drug hypothesis has been applied in pharmacological studies such as PK/PD and efficacy studies (Walker, 2004;Smith et al., 2010;Tuntland et al., 2014;Zou et al., 2020). ...
... Solid cancer drug discovery campaigns involve running PK/PD and efficacy studies in xenografted tumors in rodents. Unbound drug at the site of action (i.e., at tumors for solid cancers) is key information needed to understand/explain PK and PD relation, to estimate drug concentration needed for response (efficacy), and to predict human dose (Walker, 2004;Smith et al., 2010;Zou et al., 2012;Tuntland et al., 2014;Zou et al., 2020). Unbound drug concentration in tumors is estimated using the relation: unbound drug concentration = total drug concentration x fraction unbound (f u ). ...
Free (unbound) drug concentration at the site of action is the key determinant of biological activity since only unbound drugs can exert pharmacological and toxicological effects. Unbound drug concentration in tumors for solid cancers is needed to understand/explain/predict pharmacokinetics (PK), pharmacodynamics (PD), and efficacy relations. Fraction unbound (fu) in tumors is usually determined across several xenografted tumors derived from various cell lines in the drug discovery stage, which is time-consuming and a resource burden. In this study, we determined the fu values for a set of diverse compounds (comprising acid, base, neutral, zwitterion, and covalent drugs) across five different xenografted tumors and five commercially available mouse tissues to explore the correlation of fu between tumors and the possibility of surrogate tissue(s) for tumor fu (fu,tumor) determination. The cross-tumor comparison showed fu,tumor values across tumors are largely comparable, and systematic tissue vs. tumor comparison demonstrated only lung tissue had comparable fu to all five tumors (fu values within 2-fold change for >80% compounds in both comparisons). These results indicated mouse lung tissue can be used as a surrogate matrix for fu,tumor assay. This study will increase efficiency in fu,tumor assessment and reduce animal use (adapting the 3Rs principle: replace, reduce, and refine) in drug discovery Significance Statement The free drug concept is a well-accepted principle in drug discovery research. Currently, fu,tumor is determined in several tumors derived from different cell lines to estimate free drug concentrations of a compound. The results from this study indicated fu,tumor across xenografted tumors are comparable and fu,tumor can be estimated using a surrogate tissue, mouse lung. The results will increase efficiency in fu,tumor assessment and reduce animal use in drug discovery.
... During the drug discovery work, a lot of attention goes to the pharmacodynamics of the newly synthesized small molecules. While the promotion of a drug candidate focuses on the pharmacokinetics behavior of such molecules [38]. In-silico ADME screening was applied to the synthesized compounds to calculate the putative absorption, distribution, metabolism, and excretion properties [39]. ...
Various sets of thiazole, thiophene, and 2-pyridone ring structures containing a dimethylaniline component were
synthesized. Substituted thiazoles 2–3 and thiophenes 5–7 were produced by reacting thiocarbamoyl compound
4 with α-halogenated reagents in diferent basic conditions. Also, a series of 2-pyridone derivatives 9a–f substituted
with dimethylaniline was synthesized through Michael addition of malononitrile to α,β-unsaturated nitrile derivatives
8a–f. The synthesized products were structurally proven by spectroscopic methods such as IR, 1
H NMR, 13C NMR,
and MS data. Furthermore, the anti-cancer efcacy of the compounds was assessed using the MTT assay on two cell
lines: hepatocellular carcinoma (HepG-2) and breast cancer (MDA-MB-231). The results showed the highest growth
inhibition for derivatives 2, 6, 7, and 9c, which were further examined for their IC50 values. The IC50 for compound
2 showed equipotent activity (IC50=1.2 µM) against the HepG-2 cell line compared to Doxorubicin (IC50=1.1 µM).
Compounds 2, 6, 7 and 9c showed very good ADME assessments for further drug administration. Moreover, the PASS
theoretical prediction for the compounds showed high antimitotic and antineoplastic activities for compounds 2,
6, 7, and 9c, as well as potent inhibition activity for the insulysin enzyme (IDE). Molecular docking stimulations were
performed on CDK1/CyclinB1/CKS2 (PDB ID: 4y72) and BPTI (PDB ID: 2ra3). When docked into (PDB ID: 4y72), all
of the tested compounds showed considerable inhibition, and the 2-pyridone derivative 9d had the maximum bind‑
ing afnity (−8.1223 kcal/mol). While thiophene derivative 6 ofered the maximum binding afnity (−7.5094 kcal/mol)
when docked into (PDB ID: 2ra3).
... Interestingly, PPK/PD modeling opens a more precise way to explore the complex association between ω-3 PUFA and type 2 diabetes. PPK-PD allows precise analysis of the quantitative relationship between the analyte plasma concentration and the primary efficacy index in patients by establishing a mathematical formula, which includes the quantitative impact of demographic, clinical information, and other covariates [17]. PPK-PD has been successfully applied to drugs such as acyclovir [18], vedolizumab [19], Oxycodone [20], teicoplanin [21], providing valuable information for rational clinical use. ...
Objective
ω-3 polyunsaturated fatty acids (PUFA) are a key modifiable factor in the intervention of type 2 diabetes, yet recommendations for dietary consumption of ω-3 PUFA in type 2 diabetes remain ambiguous and controversial. Here, we revisit the subject in the light of population pharmacokinetic-pharmacodynamic (PPK-PD) modeling and propose a threshold for intake.
Research design and methods
Plasma levels of ω-3 PUFA and glycosylated hemoglobin (HbA1c) were measured as pharmacokinetic and pharmacodynamic indicator, respectively. The nonlinear mixed effect analysis was used to construct a PPK-PD model for ω-3 PUFA and to quantify the effects of FADS gene polymorphism, age, liver and kidney function, and other covariables.
Results
Data from 161 patients with type 2 diabetes in the community were modeled in a two-compartment model with primary elimination, and HDL was a statistically significant covariate. The simulation results showed that HbA1c showed a dose-dependent decrease of ω-3 PUFA plasma level. A daily intake of ω-3 PUFA at 0.4 g was sufficient to achieve an HbA1c level of 7% in more than 95% of patients.
Conclusions
PPK/PD modeling was proposed as a multilevel analytical framework to quantitatively investigate finer aspects of the complex relationship between ω-3 PUFA and type 2 diabetes on genetic and non-genetic influence factors. The results support a beneficial role for ω-3 PUFA in type 2 diabetes and suggested the intake threshold. This new approach may provide insights into the interaction of the two and an understanding of the context in which changes occur.
... According to Zou et al. [89], this model technique also finds extensive application in drug delivery systems and the modification of large molecules, both in preclinical and clinical trials, providing essential insights for animal-to-human translation and facilitating the selection of therapeutic regimens. Even at the initial stages, during the discovery of novel compounds phase, these strategies can be effectively implemented [97]. PKPD modelbased analysis enables a faster in vitro to in vivo translation, reduces the number of animal studies, and improves bench-to-bed translation. ...
The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient’s uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the “five rights”: the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug–drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.
... Measurements of drug bioavailability are essential for evaluating the pharmacokinetics and pharmacodynamics of drugs and for determining appropriate therapeutic doses. They are also crucial for developing new drugs and evaluating the efficacy of different administration forms [16,20]. ...
... Measurements of drug bioavailability are essential for evaluating the pharmacokinetics and pharmacodynamics of drugs and for determining appropriate therapeutic doses. They are also crucial for developing new drugs and evaluating the efficacy of different administration forms [16,20]. The drug is delivered directly into the systemic circulation via intravenous injection, ensuring 100% bioavailability and immediate achievement of maximum plasma concentration (cmax, tmax = 0 min). ...
... Limited information on bioavailability may be available when new drugs are marketed. Therefore, pharmacokinetic studies, which measure bioavailability, are required before a drug can be marketed [20]. ...
Drug bioavailability is a crucial aspect of pharmacology, affecting the effectiveness of drug therapy. Understanding how drugs are absorbed, distributed, metabolized, and eliminated in patients’ bodies is essential to ensure proper and safe treatment. This publication aims to highlight the relevance of drug bioavailability research and its importance in therapy. In addition to biochemical activity, bioavailability also plays a critical role in achieving the desired therapeutic effects. This may seem obvious, but it is worth noting that a drug can only produce the expected effect if the proper level of concentration can be achieved at the desired point in a patient’s body. Given the differences between patients, drug dosages, and administration forms, understanding and controlling bioavailability has become a priority in pharmacology. This publication discusses the basic concepts of bioavailability and the factors affecting it. We also looked at various methods of assessing bioavailability, both in the laboratory and in the clinic. Notably, the introduction of new technologies and tools in this field is vital to achieve advances in drug bioavailability research. This publication also discusses cases of drugs with poorly described bioavailability, providing a deeper understanding of the complex challenges they pose to medical researchers and practitioners. Simultaneously, the article focuses on the perspectives and trends that may shape the future of research regarding bioavailability, which is crucial to the development of modern pharmacology and drug therapy. In this context, the publication offers an essential, meaningful contribution toward understanding and highlighting bioavailability’s role in reliable patient treatment. The text also identifies areas that require further research and exploration.
... In other words, a drug might show sex differences in the speed in which it is metabolized and thus brain concentrations might be initially similar between males and females but then show different time courses under which levels of the drug at the target decrease faster in one sex compared with the other. Ideally, this should be tested over at least 5-6 time points, including at the time point of the maximal concentration and during the washout phase, when no drug is in the system, to understand the time course of a potential drug's effect and if multiple doses are needed over time to maintain the effect (Aarons and Ogungbenro, 2010;Tuntland et al., 2014). There are several methods to assess drug distribution in the brain (Loryan et al., 2013;Bickel, 2005). ...
... The F value, which represents drug exposure, is a critical parameter in determining pharmacokinetic feasibility and drug efficacy [32][33][34][35][36][37][38][39], as it influences the time-course of efficacy and toxicity. In the assessment of orally administered compounds, the in vivo F value and absorption rate are of considerable importance, along with in vitro solubility and dissolution rate [40]. ...
... Pharmacokinetics involves the study of the plasma concentration-time profiles of drugs in the bloodstream and tissues, encompassing factors such as absorption rate, drug concentration, and the duration of drug presence at specific locations within the body. Upon entering the systemic circulation or reaching target tissues, a compound such as a drug interacts with various proteins (e.g., receptors, enzymes, or transporters) to initiate biological events leading to a pharmacological response [34,37,39]. The distribution of a given compound in different tissues can explain its tissue-specific pharmacological response, and the relationship between the plasma and tissue levels of a drug is commonly used to optimize dosage regimens and understand pharmacodynamic outcomes [33,36,37,59]. ...
Mirabegron (MBR) is a β3-adrenoceptor agonist used for treating overactive bladder syndrome. Due to its poor solubility and low bioavailability (F), the development of novel MBR formulations has garnered increasing attention. Recently, co-amorphous dispersions of MBR, such as MBR-1,2-ethanedisulfonic acid (MBR-EFA), MBR-1,5-naphthalenedisulfonic acid (MBR-NDA), and MBR-L-pyroglutamic acid (MBR-PG), have been developed, showing improved solubility and thermodynamic stability. Nevertheless, the pharmacokinetic feasibility of these co-amorphous dispersions has not been evaluated. Therefore, this study aimed to characterize the pharmacokinetic profiles of MBR-EFA, MBR-NDA, and MBR-PG in rats and mice. Our results exhibited that relative F24h and AUC0–24h values of MBR in MBR-EFA, MBR-NDA, and MBR-PG rats were increased by 143–195% compared with the MBR rats. The absolute F24h, relative F24h, and AUC0–24h values of MBR in MBR-EFA and MBR-NDA mice were enhanced by 178–234% compared with the MBR mice. In tissue distribution, MBR was extensively distributed in the gastrointestinal tract, liver, kidneys, lung, and heart of mice. Notably, MBR distribution in the liver, kidneys, and lung was considerably high in MBR-EFA, MBR-NDA, or MBR-PG mice compared with MBR mice. These findings highlight the potential of these co-amorphous dispersions to enhance oral F of MBR.
... Pharmacokinetics and pharmacodynamics are crucial aspects of drug development, as they determine the optimal dosage, administration route, and safety of a drug in the body [85]. Traditional experimental methods for pharmacokinetics and pharmacodynamics studies can be timeconsuming and expensive and may not always provide accurate predictions of drug efficacy and safety [179,180]. ...
Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.
... The population pharmacokinetics (Pop PK) approach allows for combining blood concentration data from different clinical groups (Rajman, 2008;Tuntland et al, 2014). The objective of this study is to figure out whether dosage adjustment is necessary for the use of GTDS in the Chinese population. ...
Granisetron patches are a prolonged delivery transdermal system that is used to prevent Chemotherapy-induced nausea and vomiting (CINV). To date, no pharmacokinetics comparison between Chinese and Caucasian populations has been conducted for granisetron patches. This study focused on the ethnic differences in pharmacokinetics (PK) of granisetron transdermal delivery system (GTDS) between Chinese and Caucasians and the influence of demographic covariates on pharmacokinetics (age, weight, height, body mass index, sex). To achieve this, blood concentration data were collected from 112 Caucasian healthy subjects participating in four clinical trials and 24 Chinese healthy subjects from one clinical trial, after a single application of the granisetron transdermal delivery system. A nonlinear mixed-effects model method of Phoenix NLME software was used to establish a population pharmacokinetic (Pop PK) model for Caucasian subjects. Bootstrap and visual predictive check (VPC) were used to validate the model. Based on the analysis a one-compartment model with first-order absorption and a first-order elimination well described the PK characteristics of GTDS. The apparent systemic clearance was determined to be 31316.3 mL/h and the central compartment volume of distribution was 6299.03 L. None of the five covariates (age, weight, height, body mass index, and sex) included in the Pop PK were significant covariates affecting PK. The final Pop PK model was used to simulate the Caucasian blood concentration by applying the dosing regimen used for the Chinese population. Comparison of the simulated Caucasian PK data with observed clinical PK data from Chinese healthy subjects revealed no significant differences in the main parameters, AUC last and C avg , between the two groups. These findings suggested that no dose adjustment was required when applied to the Chinese population. In conclusion, this Pop PK study comparing the transdermal patch in Chinese and Caucasian healthy subjects provided valuable insights for optimizing dosage across ethnicities.
