Pharmacodynamic modeling of adverse effects of anti-cancer drug treatment

Label-free, real-time monitoring of cytochrome C drug responses in microdissected tumor biopsies with a multi-well aptasensor platform

Functional assays on intact tumor biopsies can complement genomics-based approaches for precision oncology, drug testing, and organs-on-chips cancer disease models by capturing key therapeutic response determinants, such as tissue architecture, tumor heterogeneity, and the tumor microenvironment. Most of these assays rely on fluorescent labeling, a semiquantitative method best suited for single-time-point assays or labor-intensive immunostaining analysis. Here, we report integrated aptamer electrochemical sensors for on-chip, real-time monitoring of cytochrome C, a cell death indicator, from intact microdissected tissues with high affinity and specificity. The platform features a multi-well sensor layout and a multiplexed electronic setup. The aptasensors measure increases in cytochrome C in the supernatant of mouse or human microdissected tumors after exposure to various drug treatments. Because of the sensor's high affinity, it primarily tracks rising concentrations of cytochrome C, capturing dynamic changes during apoptosis. This approach could help develop more advanced cancer disease models and apply to other complex in vitro disease models, such as organs-on-chips and organoids.

Label-Free, Real-Time Monitoring of Cytochrome C Responses to Drugs in Microdissected Tumor Biopsies with a Multi-Well Aptasensor Platform

Functional assays on intact tumor biopsies can potentially complement and extend genomics-based approaches for precision oncology, drug testing, and organs-on-chips cancer disease models by capturing key determinants of therapeutic response, such as tissue architecture, tumor heterogeneity, and the tumor microenvironment. Currently, most of these assays rely on fluorescent labeling, a semi-quantitative method best suited to be a single-time-point terminal assay or labor-intensive terminal immunostaining analysis. Here, we report integrated aptamer electrochemical sensors for on-chip, real-time monitoring of increases of cytochrome C, a cell death indicator, from intact microdissected tissues with high affinity and specificity. The platform features a multi-well sensor layout and a multiplexed electronic setup. The aptasensors measure increases in cytochrome C in the supernatant of mouse or human microdissected tumors after exposure to various drug treatments. Since the aptamer probe can be easily exchanged to recognize different targets, the platform could be adapted for multiplexed monitoring of various biomarkers, providing critical information on the tumor and its microenvironment. This approach could not only help develop more advanced cancer disease models but also apply to other complex in vitro disease models, such as organs-on-chips and organoids.

Exploring the Potential Role of Phytopharmaceuticals in Alleviating Toxicities of Chemotherapeutic Agents

BACKGROUND

Chemotherapy is the mainstay of cancer treatment, bringing patients optimism about recurrence and survival. However, the clinical effectiveness of chemotherapeutic drugs is frequently jeopardized by their intrinsic toxicity, resulting in side effects affecting the quality of life of cancer patients. This analysis explores the ethnopharmacological impact of phytopharmaceuticals, highlighting their traditional use in many cultures. The present study, which takes its cues from indigenous knowledge, aims to close the knowledge gap between traditional medicine and modern medicine in reducing the toxicities of chemotherapy treatments.

AIM

The present in-depth study aims to highlight the current research and upcoming developments in phytopharmaceuticals for reducing the toxicity of chemotherapeutic drugs. Further, we address the mechanisms through which phytopharmaceuticals may reduce chemotherapy-induced side effects that include nausea, vomiting, myelosuppression, nephropathy, neuropathy, and cardiotoxicity using data from a variety of preclinical and clinical investigations.

MATERIALS AND METHODS

The literature search was carried out by employing search engines such as PubMed and Google Scholar with keywords such as cancer, chemotherapy, CNS toxicity, hematopoietic toxicity, renal toxicity, GI toxicity, CNS toxicity, and phytopharmaceuticals.

RESULTS

Bioactive chemicals found in plants, such as fruits, vegetables, herbs, and spices, are being studied for their capacity to improve the safety and acceptability of chemotherapy regimens. The current review also dives into the investigation of phytopharmaceuticals as adjuvant medicines in cancer treatment, which is a viable path for addressing the pressing need to lessen chemotherapy-induced toxicities.

CONCLUSION

The present review revealed that the potential of phytopharmaceuticals in alleviating chemotherapeutic drug toxicities would pave the way for better cancer treatment and patient outcomes, harmonizing with the larger trend towards personalized and holistic approaches to chemotherapy.

Plant-Derived Extracellular Vesicles and Their Exciting Potential as the Future of Next-Generation Drug Delivery

Plant cells release tiny membranous vesicles called extracellular vesicles (EVs), which are rich in lipids, proteins, nucleic acids, and pharmacologically active compounds. These plant-derived EVs (PDEVs) are safe and easily extractable and have been shown to have therapeutic effects against inflammation, cancer, bacteria, and aging. They have shown promise in preventing or treating colitis, cancer, alcoholic liver disease, and even COVID-19. PDEVs can also be used as natural carriers for small-molecule drugs and nucleic acids through various administration routes such as oral, transdermal, or injection. The unique advantages of PDEVs make them highly competitive in clinical applications and preventive healthcare products in the future. This review covers the latest methods for isolating and characterizing PDEVs, their applications in disease prevention and treatment, and their potential as a new drug carrier, with special attention to their commercial viability and toxicological profile, as the future of nanomedicine therapeutics. This review champions the formation of a new task force specializing in PDEVs to address a global need for rigor and standardization in PDEV research.

Pd(II) and Pt(II) Trinuclear Chelates with Spermidine: Selective Anticancer Activity towards TNBC-Sensitive and -Resistant to Cisplatin

Triple-negative breast cancer (TNBC) is one of the most aggressive forms of breast cancer and constitutes 10-20% of all breast cancer cases. Even though platinum-based drugs such as cisplatin and carboplatin are effective in TNBC patients, their toxicity and development of cancer drug resistance often hamper their clinical use. Hence, novel drug entities with improved tolerability and selectivity profiles, as well as the ability to surpass resistance, are needed. The current study focuses on Pd(II) and Pt(II) trinuclear chelates with spermidine (Pd3Spd2 and Pt3Spd2) for evaluating their antineoplastic activity having been assessed towards (i) cisplatin-resistant TNBC cells (MDA-MB-231/R), (ii) cisplatin-sensitive TNBC cells (MDA-MB-231) and (iii) non-cancerous human breast cells (MCF-12A, to assess the cancer selectivity/selectivity index). Additionally, the complexes' ability to overcome acquired resistance (resistance index) was determined. This study revealed that Pd3Spd2 activity greatly exceeds that displayed by its Pt analog. In addition, Pd3Spd2 evidenced a similar antiproliferative activity in both sensitive and resistant TNBC cells (IC50 values 4.65-8.99 µM and 9.24-13.34 µM, respectively), with a resistance index lower than 2.3. Moreover, this Pd compound showed a promising selectivity index ratio: >6.28 for MDA-MB-231 cells and >4.59 for MDA-MB-231/R cells. Altogether, the data presently gathered reveal Pd3Spd2 as a new, promising metal-based anticancer agent, which should be further explored for the treatment of TNBC and its cisplatin-resistant forms.

Engineered macrophages acting as a trigger to induce inflammation only in tumor tissues based on arginase 1-responsive TNF-α accelerated release

Herein, we report engineered macrophages, termed "MacTrigger," acting as a trigger to induce an inflammatory environment only in tumor tissues. This led to intensive anti-tumor effects based on the removal potential of foreign substances. The strength of this study is the utilization of two unique functions of macrophages: (1) their ability to migrate to tumor tissues and (2) polarization into the anti-inflammatory M2 phenotype in the presence of tumor tissues. The MacTrigger accelerated the release of inflammatory cytokines, tumor necrosis factor-alpha (TNF-α), when it was polarized to the M2 phenotype. When the MacTrigger was administered to tumor-bearing mice, tumor growth was significantly inhibited compared with the non-treatment group, the un-transfected macrophages group, and the group with engineered macrophages capable of randomly releasing TNF-α. Additionally, the ratio of the M1 phenotype to the M2 phenotype in tumor tissues was >1 only in the MacTrigger group. Moreover, the ratios of natural killer cells and CD8⁺T cells in tumor tissues were increased compared with other groups. These results indicate that MacTrigger can induce inflammation in tumor tissues, leading to effective anti-tumor effects. In normal tissues, especially the liver, notable side effects were not observed. This is because, in the liver, the MacTrigger was not polarized to the M2 phenotype and could not induce inflammation. These results suggest that the MacTrigger is a "trigger" that can induce inflammation only in tumor tissues, then allowing the body to attack tumor tissues through the innate immunity system.

A comprehensive regulatory and industry review of modeling and simulation practices in oncology clinical drug development

Exposure-response (E-R) analyses are an integral component in the development of oncology products. Characterizing the relationship between drug exposure metrics and response allows the sponsor to use modeling and simulation to address both internal and external drug development questions (e.g., optimal dose, frequency of administration, dose adjustments for special populations). This white paper is the output of an industry-government collaboration among scientists with broad experience in E-R modeling as part of regulatory submissions. The goal of this white paper is to provide guidance on what the preferred methods for E-R analysis in oncology clinical drug development are and what metrics of exposure should be considered.

Myelotoxicity of Temozolomide Treatment in Patients with Glioblastoma Is It Time for a More Mechanistic Approach?

Glioblastoma multiforme is the most common primary central nervous system tumor, with an incidence of 3 [...].

Pharmacometric modeling of drug adverse effects: an application of mixture models in schizophrenia spectrum disorder patients treated with clozapine

Clozapine has superior efficacy to other antipsychotics yet is underutilized due to its adverse effects, such as neutropenia, weight gain, and tachycardia. The current investigation aimed to introduce a pharmacometric approach to simultaneously model drug adverse effects, with examples from schizophrenia spectrum patients receiving clozapine. The adverse drug effects were represented as a function of time by incorporating a mixture model to describe individual susceptibility to the adverse effects. Applications of the proposed method were presented by analyzing retrospective data from patients' medical records in Psychiatric Clinic, Penang General Hospital. Tachycardia, weight gain, and absolute neutrophils count (ANC) decrease were best described by an offset, a piecewise linear, and a transient surge function, respectively. 42.9% of the patients had all the adverse effects, including weight gain (0.01 kg/m² increase every week over a baseline of 24.7 kg/m² until stabilizing at 279 weeks), ANC decrease (20% decrease from 4540 cells/µL week 12-20.8), and tachycardia (14% constant increase over a baseline of 87.9 bpm for a clozapine maintenance dose of 450 mg daily). 32.5% of the patients had only tachycardia, while the remaining 24.6% had none of the adverse effects. A new pharmacometric approach was proposed to describe adverse drug effects with examples of clozapine-induced weight gain, ANC drop, and tachycardia. The current approach described the longitudinal time changes of continuous data while assessing patient susceptibility. Furthermore, the model revealed the possible co-existence of ANC drop and weight gain; thus, neutrophil monitoring might predict future changes in body weight.

The Structural Characteristics of an Acidic Water-Soluble Polysaccharide from Bupleurum chinense DC and Its In Vivo Anti-Tumor Activity on H22 Tumor-Bearing Mice

This study explored the preliminary structural characteristics and in vivo anti-tumor activity of an acidic water-soluble polysaccharide (BCP) separated purified from Bupleurum chinense DC root. The preliminary structural characterization of BCP was established using UV, HPGPC, FT-IR, IC, NMR, SEM, and Congo red. The results showed BCP as an acidic polysaccharide with an average molecular weight of 2.01 × 10³ kDa. Furthermore, we showed that BCP consists of rhamnose, arabinose, galactose, glucose, and galacturonic acid (with a molar ratio of 0.063:0.788:0.841:1:0.196) in both α- and β-type configurations. Using the H22 tumor-bearing mouse model, we assessed the anti-tumor activity of BCP in vivo. The results revealed the inhibitory effects of BCP on H22 tumor growth and the protective actions against tissue damage of thymus and spleen in mice. In addition, the JC-1 FITC-AnnexinV/PI staining and cell cycle analysis have collectively shown that BCP is sufficient to induce apoptosis and of H22 hepatocarcinoma cells in a dose-dependent manner. The inhibitory effect of BCP on tumor growth was likely attributable to the S phase arrest. Overall, our study presented significant anti-liver cancer profiles of BCP and its promising therapeutic potential as a safe and effective anti-tumor natural agent.

The Effect of CHIR 99021, a Glycogen Synthase Kinase-3β Inhibitor, on Transforming Growth Factor β-Induced Tenon Fibrosis

Purpose

This study investigated the effect of glycogen synthase kinase-3β (GSK-3β) inhibition on the fibrosis of human Tenon's fibroblasts (HTFs) induced by transforming growth factor-β (TGF-β).

Methods

Quantitative real-time PCR and Western blot analyses were performed to determine the expression levels of molecules associated with the fibrosis of HTFs by TGF-β (fibronectin, collagen Iα, and α-smooth muscle actin) and GSK-3β. The levels of phosphorylated Smad2 and Smad3 were also analyzed in the presence of the GSK-3β inhibitor CHIR 99021. The wound healing assay was performed to determine the effect of CHIR 99021 on the migration of HTFs. All experiments were conducted using primary cultured HTFs or human tenon tissues obtained from normal subjects and patients with glaucoma.

Results

Treatment with TGF-β resulted in an increase in the levels of molecules associated with the fibrosis of HTFs. The expression levels of these molecules were higher in the tenon tissues obtained from patients with glaucoma than those from normal subjects. When the HTFs were treated with TGF-β, a significant increase in the active form of GSK-3β (Y216) was observed. A significant decrease in the active form of GSK-3β and molecules associated with fibrosis by TGF-β was noted in HTFs treated with CHIR 99021. CHIR 99021 treatment reduced the phosphorylated Smad2/Smad2 and phosphorylated Smad3/Smad3 ratios in HTFs and attenuated HTF migration.

Conclusions

Our results demonstrated the effect of GSK-3β inhibition on the regulation of TGF-β–mediated fibrosis of HTFs, suggesting GSK-3β to be a potential target for maintaining bleb function after glaucoma filtration surgery.

Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

Targeted PD-L1 PLGA/liposomes-mediated luteolin therapy for effective liver cancer cell treatment

Stealth PLGA/Liposome nanoparticles (NPs) modified with tumor-targeting PD-L1 antibody for systemic delivery of luteolin for liver cancer were prepared. The morphologies and therapeutic effects of luteolin-loaded PD-L1 targeted stealth PLGA/Liposomes (L-PD-SP/Ls) in vitro were analyzed. Functional L-PD-P/L NPs composed of PLGA, DOPC and DSPE-PEG display low cell cytoxicity in HepG2 cells, and has more cell uptake ability than P/Ls NPs. L-PD-SP/Ls was more effective in inhibiting HepG2 cell proliferation than free luteolin in solution (p < 0.05) and luteolin-loaded P/Ls (p < 0.05). Compared with the cell control group and the non-PD-L1 targeted group, the mediated effect of PD-L1 can significantly enhance the uptake of drugs by cells, and L-PD-SP/Ls can significantly reduce the expression of Bcl-2 and increase the level of LDH in cells. Our findings collectively support the utility of PD-L1-targeted P/L NPs as a potentially effective drug delivery system.

Therapeutic Apheresis, Circulating PLD, and Mucocutaneous Toxicity: Our Clinical Experience through Four Years

Cancer treatment has been greatly improved by the combined use of targeted therapies and novel biotechnological methods. Regarding the former, pegylated liposomal doxorubicin (PLD) has a preferential accumulation within cancer tumors, thus having lower toxicity on healthy cells. PLD has been implemented in the targeted treatment of sarcoma, ovarian, breast, and lung cancer. In comparison with conventional doxorubicin, PLD has lower cardiotoxicity and hematotoxicity; however, PLD can induce mucositis and palmo-plantar erythrodysesthesia (PPE, hand-foot syndrome), which limits its use. Therapeutical apheresis is a clinically proven solution against early PLD toxicity without hindering the efficacy of the treatment. The present review summarizes the pharmacokinetics and pharmacodynamics of PLD and the beneficial effects of extracorporeal apheresis on the incidence of PPE during chemoradiotherapy in cancer patients.

Machine Learning Approach to Forecast Chemotherapy-Induced Haematological Toxicities in Patients with Rhabdomyosarcoma

Developing precision medicine is a major trend in clinical oncology. The main adverse effects of ifosfamide, actinomycin D and vincristine (IVA) treatment for rhabdomyosarcoma are haematological toxicities such as neutropenia or thrombocytopenia. The severity of these effects vary among patients but their dynamic profiles are similar. A non-empirical adjustment of the chemotherapy dose to avoid severe toxicities could help secure the treatment administration. Twenty-four patients with rhabdomyosarcoma treated with IVA chemotherapy courses were selected. Before and during each cycle, routine multiple blood cell counts were performed allowing for a dynamic study of the haematological toxicities. We developed a machine learning analysis using a gradient boosting regression technique to forecast the ifosfamide induced haematological toxicities as a function of neutrophils and platelets initial levels and the initial ifosfamide dose. To validate models’ accuracy, predicted and observed neutrophils and platelets levels were compared. The model was able to reproduce the dynamic profiles of the haematological toxicities. Among all cycles, the mean absolute errors between predicted and observed neutrophils and platelets levels were 1.0 and 72.8 G/L, respectively. Adjusting a patient’s ifosfamide dose based upon the predicted haematological toxicity levels at the end of a treatment cycle could enable tailored treatment.

Quantification of the pharmacokinetic-toxicodynamic relationship of oral docetaxel co-administered with ritonavir

Introduction Oral formulations of docetaxel have successfully been developed as an alternative for intravenous administration. Co-administration with the enzyme inhibitor ritonavir boosts the docetaxel plasma exposure. In dose-escalation trials, the maximum tolerated doses for two different dosing regimens were established and dose-limiting toxicities (DLTs) were recorded. The aim of current analysis was to develop a pharmacokinetic (PK)-toxicodynamic (TOX) model to quantify the relationship between docetaxel plasma exposure and DLTs. Methods A total of 85 patients was included in the current analysis, 18 patients showed a DLT in the four-week observation period. A PK-TOX model was developed and simulations based on the PK-TOX model were performed. Results The final PK-TOX model was characterized by an effect compartment representing the toxic effect of docetaxel, which was linked to the probability of developing a DLT. Simulations of once-weekly, once-daily 60 mg and once-weekly, twice-daily 30 mg followed by 20 mg of oral docetaxel suggested that 14% and 34% of patients, respectively, would have a probability >25% to develop a DLT in a four-week period. Conclusions A PK-TOX model was successfully developed. This model can be used to evaluate the probability of developing a DLT following treatment with oral docetaxel and ritonavir in different dosing regimens.

Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients

Pretomanid (PA-824) is a nitroimidazole in clinical testing for the treatment of tuberculosis. A population pharmacodynamic model for pretomanid was developed using a Bayesian analysis of efficacy data from two early bactericidal activity (EBA) studies, PA-824-CL-007 and PA-824-CL-010, conducted in Cape Town, South Africa. The two studies included 122 adult male and female participants with newly diagnosed pulmonary tuberculosis who received once daily oral pretomanid doses of either 50, 100, 150, 200, 600, 1,000, or 1,200 mg for 14 days. The structural model described capacity-limited growth and saturable drug-induced bacterial killing with separate rate equations for sputum solid culture colony forming unit (CFU) counts and liquid culture time to positivity (TTP) that were linked through a time constant. The posterior population geometric means and interindividual variability percent coefficients of variation were, respectively; 0.152±0.013 log₁₀ CFU/mL sputum/day and 54%±6% for the maximum kill rate constant, 20.4±1.0 h and 20.8%±0.1% for the time constant of proportionality between the CFU and TTP rate equations, and 770±140 ng/mL and 48%±17% for the pretomanid half-maximum effect plasma concentration. Model simulations showed once daily pretomanid at 100 mg, 200 mg, and 300 mg, attained 58%, 73%, and 80%, respectively, of an expected maximum 14-day EBA of 0.136 log₁₀CFU/mL sputum/day. These results establish a pretomanid exposure-efficacy relationship with dual outcomes for CFU counts and TTP, and with potential applications to dose optimization of pretomanid-containing regimens.

Understanding Hematological Toxicities Using Mathematical Modeling

Balancing antitumor efficacy with toxicity is a significant challenge, and drug-induced myelosuppression is a common dose-limiting toxicity of cancer treatments. Mathematical modeling has proven to be a powerful ally in this field, scaling results from animal models to humans, and designing optimized treatment regimens. Here we outline existing mathematical approaches for studying bone marrow toxicity, identify gaps in current understanding, and make future recommendations to advance this vital field of safety research further.

Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients

Human primary glioblastomas (GBM) often harbor mutations within the epidermal growth factor receptor (EGFR). Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.

Towards Quantitative Systems Pharmacology Models of Chemotherapy-Induced Neutropenia

Neutropenia is a serious toxic complication of chemotherapeutic treatment. For years, mathematical models have been developed to better predict hematological outcomes during chemotherapy in both the traditional pharmaceutical sciences and mathematical biology disciplines. An increasing number of quantitative systems pharmacology (QSP) models that combine systems approaches, physiology, and pharmacokinetics/pharmacodynamics have been successfully developed. Here, I detail the shift towards QSP efforts, emphasizing the importance of incorporating systems-level physiological considerations in pharmacometrics.