A Novel Integrated Pharmacokinetic-Pharmacodynamic Model to Evaluate Combination Therapy and Determine In Vivo Synergism

Drug-Drug Interactions and Synergy: From Pharmacological Models to Clinical Application

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. SIGNIFICANCE STATEMENT: Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug-drug interactions research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.

Translational Pharmacokinetic-Toxicodynamic Model of Myelosuppression for Dose Optimization in Combination Chemotherapy of Capecitabine and Oxaliplatin from Rats to Humans

XELOX therapy, which comprises capecitabine and oxaliplatin, is the standard first-line chemotherapeutic regimen for colorectal cancer. However, its myelosuppressive effects pose challenges for its clinical management. Mathematical modeling combining pharmacokinetics (PK) and toxicodynamics (TD) is a promising approach for optimizing dosing strategies and reducing toxicity. This study aimed to develop a translational PK-TD model using rat data to inform dosing strategies and TD implications in humans. The rats were administered capecitabine, oxaliplatin, or XELOX combination regimen, and PK and TD data were collected. PK parameters were analyzed using sequential compartment analysis, whereas TD responses were assessed using Friberg's semiphysiological model. A toxicity intensity-based nomogram recommends optimal dosing strategies. Translational modeling techniques using the hybrid PK-TD model were employed to predict clinical responses. The PK-TD model successfully predicted the time-course profiles of hematological responses in rats following monotherapy and XELOX combination treatment. Interactive effects on lymphocytopenia were identified with the coadministration of capecitabine and oxaliplatin. A model-based recommended combination of the dose reduction rate for escaping severe lymphocytopenia was proposed as 40% and 60% doses of capecitabine and oxaliplatin, respectively. The current translational model techniques successfully simulated the time-course profiles of blood cell counts with confidence intervals in patients using rat data. Our study provides valuable insights into dose optimization strategies for each individual drug within the XELOX regimen and underscores the potential of translational modeling to improve patient outcomes. In addition to dose determination, these data will lay the groundwork for advancing drug development processes in oncology. SIGNIFICANCE STATEMENT: This study introduced a novel translational modeling approach rooted in a rat PK-TD model to optimize dosing strategies for the XELOX regimen for colorectal cancer treatment. Our findings highlight the interactive effects on lymphocytopenia and suggest a toxicity intensity-based nomogram for dose reduction, thus advancing precision medicine. This translational modeling paradigm enhances our understanding of drug interactions, offering a tool to tailor dosing, minimize hematological toxicity, and improve therapeutic outcomes in patients undergoing XELOX therapy.

Nanoparticles for Augmenting Therapeutic Potential and Alleviating the Effect of Di(2-ethylhexyl) Phthalate on Gastric Cancer

Changes in diet culture and modern lifestyle contributed to a higher incidence of gastrointestinal-related diseases, including gastritis, implicated in the pathogenesis of gastric cancer. This observation raised concerns regarding exposure to di(2-ethylhexyl) phthalate (DEHP), which is linked to adverse health effects, including reproductive and developmental problems, inflammatory response, and invasive adenocarcinoma. Research on the direct link between DEHP and gastric cancer is ongoing, and further studies are required to establish a conclusive association. In our study, extremely low concentrations of DEHP exerted significant effects on cell migration by promoting the epithelial-mesenchymal transition in gastric cancer cells. This effect was mediated by the modulation of the PI3K/AKT/mTOR and Smad2 signaling pathways. To address the DEHP challenges, our initial design of TPGS-conjugated fucoidan, delivered via pH-responsive nanoparticles, successfully demonstrated binding to the P-selectin protein. This achievement has not only enhanced the antigastric tumor efficacy but has also led to a significant reduction in the expression of malignant proteins associated with the condition. These findings underscore the promising clinical therapeutic potential of our approach.

Translational PK-PD/TD modeling of antitumor effects and peripheral neuropathy in gemcitabine and nab-paclitaxel chemotherapy from xenograft mice to patients for optimal dose and schedule

PURPOSE

Gemcitabine and nab-paclitaxel (GnP) treatment, the standard first-line chemotherapy for unresectable pancreatic cancer, often causes peripheral neuropathy (PN). To develop alternative dosing strategies to avoid severe PN, understanding the relationship between pharmacokinetics (PK) and pharmacodynamics/toxicodynamics (PD/TD) is necessary. We established a PK-PD/TD model of GnP treatment to develop an optimal dose schedule.

METHODS

A mouse xenograft model of human pancreatic cancer was generated to measure drug concentrations in the plasma and tumor, antitumor effects, and PN after GnP treatment. The Simeoni tumor growth inhibition model with tumor concentrations and empirical indirect response models were used for the PD and TD models, respectively. Clinical outcomes were predicted with reported population estimates of PK parameters in cancer patients.

RESULTS

The PK-PD/TD model simultaneously described the observed tumor volume and paw withdrawal frequency in the von Frey test. For the standard GnP regimen, the model predicted clinical overall response (75.1%), which was overestimated compared to that in a recent phase II study (42.1%) but lower than the observed disease control rate (96.5%). Model simulation showed that dose reduction to less than 40% GnP dose was not effective; a change of dose schedule from every week for 3 weeks to every 2 weeks was a more favorable approach than dose reduction to 60% every week.

CONCLUSION

The PK-PD/TD model-based translational approach provides a guide for optimal dose determination to avoid severe PN while maintaining antitumor effects during GnP chemotherapy. Further research is needed to enhance its applicability and potential for combination chemotherapy regimens.

No Interference of H9 Extract on Trastuzumab Pharmacokinetics in Their Combinations

Trastuzumab is used to treat breast cancer patients overexpressing human epidermal growth factor receptor 2, but resistance and toxicity limit its uses, leading to attention to trastuzumab combinations. Recently, the synergistic effect of trastuzumab and H9 extract (H9) combination against breast cancer has been reported. Because drug exposure determines its efficacy and toxicity, the question of whether H9 changes trastuzumab exposure in the body has been raised. Therefore, this study aimed to characterize trastuzumab pharmacokinetics and elucidate the effect of H9 on trastuzumab pharmacokinetics at a combination dose that shows synergism in mice. As a result, trastuzumab showed linear pharmacokinetics after its intravenous administration from 1 to 10 mg/kg. In the combination of trastuzumab and H9, single and 2-week treatments of oral H9 (500 mg/kg) did not influence trastuzumab pharmacokinetics. In the multiple-combination treatments of trastuzumab and H9 showing their synergistic effect (3 weeks of trastuzumab with 2 weeks of H9), the pharmacokinetic profile of trastuzumab was comparable to that of 3 weeks of trastuzumab alone. In tissue distribution, the tissue to plasma ratios of trastuzumab below 1.0 indicated its limited distributions within the tissues, and these patterns were unaffected by H9. These results suggest that the systemic and local exposures of trastuzumab are unchanged by single and multiple-combination treatments of H9.

Zhuidu Formula suppresses the migratory and invasive properties of triple-negative breast cancer cells via dual signaling pathways of RhoA/ROCK and CDC42/MRCK

ETHNOPHARMACOLOGICAL RELEVANCE

Zhuidu Formula (ZDF) is composed of triptolide, cinobufagin and paclitaxel, which are the active ingredients of Tripterygium wilfordii Hook. F, dried toad skin and Taxus wallichiana var. chinensis (Pilg) Florin, respectively. Modern pharmacological studies show that triptolide, cinobufagin, and paclitaxel are well-known natural compounds that exert anti-tumor effects by interfering with DNA synthesis, inducing tumor cell apoptosis, and inhibiting the dynamic balance of the tubulin. However, the mechanism by which the three compounds inhibit triple-negative breast cancer (TNBC) metastasis is unknown.

OBJECTIVE

The objective of this investigation was to examine the inhibitory essences of ZDF on the metastasis of TNBC and elucidate its potential mechanism.

MATERIALS AND METHODS

Cell viability of triptolide (TPL), cinobufagin (CBF), and paclitaxel (PTX) on MDA-MB-231 cells was assessed employing a CCK-8 assay. The drug interactions of the three drugs on MDA-MB-231 cells were determined in vitro utilizing the Chou-Talalay method. MDA-MB-231 cells were identified for migration, invasion and adhesion in vitro through the implementation of the scratch assay, transwell assay and adhesion assay, respectively. The formation of cytoskeleton protein F-actin was detected by immunofluorescence assay. The expressions of MMP-2 and MMP-9 in the supernatant of the cells were determined by ELISA analysis. The Western blot and RT-qPCR were employed to explore the protein expressions associated with the dual signaling pathways of RhoA/ROCK and CDC42/MRCK. The anti-tumor efficacy of ZDF in vivo and its preliminary mechanism were investigated in the mouse 4T1 TNBC model.

RESULTS

The results demonstrated that ZDF could significantly reduce the viability of the MDA-MB-231 cell, and the combination index (CI) values of actual compatibility experimental points were all less than 1, demonstrating a favorable synergistic compatibility relationship. It was found that ZDF reduces RhoA/ROCK and CDC42/MRCK dual signaling pathways, which are responsible for MDA-MB-231cell migration, invasion, and adhesion. Additionally, there has been a significant reduction in the manifestation of cytoskeleton-related proteins. Furthermore, the expression levels of RhoA, CDC42, ROCK2, and MRCKβ mRNA and protein were down-regulated. ZDF significantly decreased the protein expressions of vimentin, cytokeratin-8, Arp2 and N-WASP, and inhibited actin polymerization and actomyosin contraction. Furthermore, MMP-2 and MMP-9 levels in the high-dose ZDF group were decreased by 30% and 26%, respectively. ZDF significantly reduced the tumor volume and protein expressions of ROCK2 and MRCKβ in tumor tissues without eliciting any perceptible alterations in the physical mass of the mice, and the reduction was more pronounced than that of the BDP5290 treated group.

CONCLUSION

The current investigation demonstrates that ZDF exhibits a proficient inhibitory impact on TNBC metastasis by regulating cytoskeletal proteins through the dual signaling pathways of RhoA/ROCK and CDC42/MRCK. Furthermore, the findings indicate that ZDF has significant anti-tumorigenic and anti-metastatic characteristics in breast cancer animal models.

Pharmacokinetic/Pharmacodynamic Analysis of Savolitinib plus Osimertinib in an EGFR Mutation-Positive, MET-Amplified Non-Small Cell Lung Cancer Model

Osimertinib is a third-generation, irreversible, oral EGFR tyrosine kinase inhibitor (TKI) recommended as first-line treatment for patients with locally advanced/metastatic EGFR mutation-positive (EGFRm) non-small cell lung cancer (NSCLC). However, MET amplification/overexpression is a common acquired osimertinib resistance mechanism. Savolitinib is an oral, potent, and highly selective MET-TKI; preliminary data suggest that combining osimertinib with savolitinib may overcome MET-driven resistance. A patient-derived xenograft (PDX) mouse model with EGFRm, MET-amplified NSCLC was tested with a fixed osimertinib dose [10 mg/kg for exposures equivalent to (≈)80 mg], combined with doses of savolitinib (0-15 mg/kg, ≈0-600 mg once daily), both with 1-aminobenzotriazole (to better match clinical half-life). After 20 days of oral dosing, samples were taken at various time points to follow the time course of drug exposure in addition to phosphorylated MET and EGFR (pMET and pEGFR) change. Population pharmacokinetics, savolitinib concentration versus percentage inhibition from baseline in pMET, and the relationship between pMET and tumor growth inhibition (TGI) were also modeled. As single agents, savolitinib (15 mg/kg) showed significant antitumor activity, reaching ∼84% TGI, and osimertinib (10 mg/kg) showed no significant antitumor activity (34% TGI, P > 0.05 vs. vehicle). Upon combination, at a fixed dose of osimertinib, significant savolitinib dose-related antitumor activity was shown, ranging from 81% TGI (0.3 mg/kg) to 84% tumor regression (15 mg/kg). Pharmacokinetic-pharmacodynamic modeling showed that the maximum inhibition of both pEGFR and pMET increased with increasing savolitinib doses. Savolitinib demonstrated exposure-related combination antitumor activity when combined with osimertinib in the EGFRm MET-amplified NSCLC PDX model.

Protein Binding in Translational Antimicrobial Development-Focus on Interspecies Differences

Background/Introduction: Plasma protein binding (PPB) continues to be a key aspect of antibiotic development and clinical use. PPB is essential to understand several properties of drug candidates, including antimicrobial activity, drug-drug interaction, drug clearance, volume of distribution, and therapeutic index. Focus areas of the review: In this review, we discuss the basics of PPB, including the main drug binding proteins i.e., Albumin and α-1-acid glycoprotein (AAG). Furthermore, we present the effects of PPB on the antimicrobial activity of antibiotics and the current role of PPB in in vitro pharmacodynamic (PD) models of antibiotics. Moreover, the effect of PPB on the PK/PD of antibiotics has been discussed in this review. A key aspect of this paper is a concise evaluation of PPB between animal species (dog, rat, mouse, rabbit and monkey) and humans. Our statistical analysis of the data available in the literature suggests a significant difference between antibiotic binding in humans and that of dogs or mice, with the majority of measurements from the pre-clinical species falling within five-fold of the human plasma value. Conversely, no significant difference in binding was found between humans and rats, rabbits, or monkeys. This information may be helpful for drug researchers to select the most relevant animal species in which the metabolism of a compound can be studied for extrapolating the results to humans. Furthermore, state-of-the-art methods for determining PPB such as equilibrium dialysis, ultracentrifugation, microdialysis, gel filtration, chromatographic methods and fluorescence spectroscopy are highlighted with their advantages and disadvantages.

Pharmacokinetic-pharmacodynamic modeling analysis for hydroxysafflor yellow A-calycosin in compatibility in normal and cerebral ischemic rats: A comparative study

OBJECTIVE

Astragalus and Safflower are commonly used in the treatment of stroke. Studies have shown that their two active components, hydroxysafflor yellow A (HSYA) and calycosin (CA), have protective effects on cerebral ischemia-reperfusion injury (I/R). However, the pharmacokinetic-pharmacodynamic (PK-PD) modeling study of the combination of the two components has not been reported in rats. The study aimed to perform combined PK-PD modeling of HSYA and CA in normal and cerebral ischemia model rats to explain quantitatively their time-concentration-effect relationship.

METHODS

To make the middle cerebral artery occlusion (MCAO) model. SD rats were randomly divided into normal treated group (NTG) (n = 6), model group (MDG) (n = 6) and model treated group (MTG) (n = 6). Plasma was collected from the mandibular vein after 0, 2, 5, 10, 15, 20, 30, 45, 60, 75, 90, 120, 180, and 240 min after intravenous administration. Rats in NTG and MTG were administered the same dose of HSYA (5 mg/kg) and CA (8 mg/kg) by tail vein injection. HPLC-VWD method was used for detection and analysis. Simultaneously, ELISA was performed to detect the levels of IL-1β and caspase-9 in rat plasma at different time points. The improvement in the above indicators was compared after administration. Lastly, after combining the pharmacokinetic parameters and pharmacodynamic indicators in vivo, DAS 3.2.6 software was used to fit the PK-PD model.

RESULTS

The MCAO model was successfully established. Compared to NTG, there was a significant difference (P < 0.05) in t_1/2α, t_1/2β, V₁, V₂, CL₁, CL₂, AUC_(0-t), AUC _(0-∞), and K₁₂ of MTG for HSYA, and there was a significant difference (P < 0.05) in t_1/2α, V₁, CL₁, AUC_(0-t), AUC _(0-∞), and K₁₀ of MTG for CA_. Compared to NTG, the PK parameters of t_1/2α, V₁, V₂, CL₁, and K₁₀ were higher for HSYA in MTG, while AUC_(0-t), AUC _(0-∞), K₁₂, and K₂₁ were lower; the PK parameters of t_1/2α, V₁, V₂, AUC_(0-t), and AUC_(0-∞) were higher for CA in MTG, while CL₁, CL₂, K₁₀, K₁₂, and K₂₁ were lower. Also, the results of PD showed extremely significant differences in the levels of caspase-9 and IL-1β at the different time points in MTG (P < 0.01) compared with 0 min. The levels of caspase-9 and IL-1β in NTG rats showed little fluctuation and were relatively stable; however, their levels in MTG showed a downward trend with time. There were highly significant differences in the levels of each of the pharmacodynamic indicators at every time point between NTG and MTG (P < 0.01).

CONCLUSION

The PK-PD model of the combined administration of HSYA and CA was successfully established in rats, and the differences in pharmacodynamic and pharmacokinetic properties between the normal and cerebral ischemic rats were evaluated. Based on comprehensive data analysis, we found that the combination of HSYA and CA may exert protective effects against I/R injury in rats via anti-apoptotic and anti-inflammatory pathways. The study provided additional insights into the development of drugs for ischemic stroke as well as the design of appropriate dosing regimens.

Using mathematical modeling to estimate time-independent cancer chemotherapy efficacy parameters

One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-cancer drugs are often not selective and cause damage to healthy cells, leading to serious side effects for patients. For this reason more targeted therapeutics and drug delivery methods are being developed. The effectiveness of new treatments is initially determined via in vitro cell viability assays, which determine the IC 50  of the drug. However, these assays are known to result in estimates of IC 50  that depend on the measurement time, possibly resulting in over- or under-estimation of the IC 50 . Here, we test the possibility of using cell growth curves and fitting of mathematical models to determine the IC 50  as well as the maximum efficacy of a drug ( ε max ). We measured cell growth of MCF-7 and HeLa cells in the presence of different concentrations of doxorubicin and fit the data with a logistic growth model that incorporates the effect of the drug. This method leads to measurement time-independent estimates of IC 50  and ε max , but we find that ε max  is not identifiable. Further refinement of this methodology is needed to produce uniquely identifiable parameter estimates.