The rationale of dose-response curves in selecting cancer drug dosing

Cellular Kinetics and Biodistribution of Adoptive T Cell Therapies: from Biological Principles to Effects on Patient Outcomes

Cell-based immunotherapy has revolutionized cancer treatment in recent years and is rapidly expanding as one of the major therapeutic options in immuno-oncology. So far ten adoptive T cell therapies (TCTs) have been approved by the health authorities for cancer treatment, and they have shown remarkable anti-tumor efficacy with potent and durable responses. While adoptive T cell therapies have shown success in treating hematological malignancies, they are lagging behind in establishing promising efficacy in treating solid tumors, partially due to our incomplete understanding of the cellular kinetics (CK) and biodistribution (including tumoral penetration) of cell therapy products. Indeed, recent clinical studies have provided ample evidence that CK of TCTs can influence clinical outcomes in both hematological malignancies and solid tumors. In this review, we will discuss the current knowledge on the CK and biodistribution of anti-tumor TCTs. We will first describe the typical CK and biodistribution characteristics of these "living" drugs, and the biological factors that influence these characteristics. We will then review the relationships between CK and pharmacological responses of TCT, and potential strategies in enhancing the persistence and tumoral penetration of TCTs in the clinic. Finally, we will also summarize bioanalytical methods, preclinical in vitro and in vivo tools, and in silico modeling approaches used to assess the CK and biodistribution of TCTs.

Resistance Management for Cancer: Lessons from Farmers

One of the main reasons we have not been able to cure cancers is that treatments select for drug-resistant cells. Pest managers face similar challenges with pesticides selecting for pesticide-resistant insects, resulting in similar mechanisms of resistance. Pest managers have developed 10 principles that could be translated to controlling cancers: (i) prevent onset, (ii) monitor continuously, (iii) identify thresholds below which there will be no intervention, (iv) change interventions in response to burden, (v) preferentially select nonchemical control methods, (vi) use target-specific drugs, (vii) use the lowest effective dose, (viii) reduce cross-resistance, (ix) evaluate success based on long-term management, and (x) forecast growth and response. These principles are general to all cancers and cancer drugs and so could be employed broadly to improve oncology. Here, we review the parallel difficulties in controlling drug resistance in pests and cancer cells. We show how the principles of resistance management in pests might be applied to cancer. Integrated pest management inspired the development of adaptive therapy in oncology to increase progression-free survival and quality of life in patients with cancers where cures are unlikely. These pest management principles have the potential to inform clinical trial design.

Multi-output prediction of dose-response curves enables drug repositioning and biomarker discovery

Drug response prediction is hampered by uncertainty in the measures of response and selection of doses. In this study, we propose a probabilistic multi-output model to simultaneously predict all dose-responses and uncover their biomarkers. By describing the relationship between genomic features and chemical properties to every response at every dose, our multi-output Gaussian Process (MOGP) models enable assessment of drug efficacy using any dose-response metric. This approach was tested across two drug screening studies and ten cancer types. Kullback-leibler divergence measured the importance of each feature and identified EZH2 gene as a novel biomarker of BRAF inhibitor response. We demonstrate the effectiveness of our MOGP models in accurately predicting dose-responses in different cancer types and when there is a limited number of drug screening experiments for training. Our findings highlight the potential of MOGP models in enhancing drug development pipelines by reducing data requirements and improving precision in dose-response predictions.

Development of nanobiosensor for therapeutic drug monitoring in personalized cancer treatment approach

Docetaxel is one of the most effective and safe chemotherapy drugs according to the World Health Organization, but its clinical use has been discontinued due to its various side effects. To reduce these side effects, the amount of docetaxel drug should be kept at the most effective level, it should be monitored in body fluids. Due to the limitations of traditional analytical methods used for this purpose, such as expensive and low sensitivity, labor-intensive and time-consuming complex preliminary preparation, efficient methods are required for the determination of the docetaxel level in the body. The increasing demand for the development of personalized therapy has recently spurred significant research into biosensors for the detection of drugs and other chemical compounds. In this study, an electrochemical-based portable nanobiosensor system was developed for the rapid, low-cost, and sensitive determination of docetaxel. In this context, mg-p(HEMA)-IMEO nanoparticles to be used as nanobiosensor bioactive layer was synthesized, characterized, and docetaxel determination conditions were optimized. According to the results obtained, the developed nanobiosensor system can detect docetaxel with a sensitivity of 2.22 mg/mL in a wide calibration range of 0.25-10 mg/mL, in only 15 min, in mixed media such as commercially available artificial blood serum and urine. determined. We concluded that the developed nanobiosensor system can be successfully used in routine drug monitoring as a low-cost biomedical device capable of direct, rapid, and specific drug determination within the scope of personalized treatment, providing point-of-care testing.

Adjustment of creatinine clearance for carboplatin dosing in Calvert's formula and clinical efficacy for lung cancer

BACKGROUND

The Cockcroft-Gault formula is commonly used as a substitute for glomerular filtration rate (GFR) in Calvert's formula for carboplatin dosing, where adjusting serum creatinine measured using the enzymatic method with 0.2 mg/dL has been suggested in Japan. However, the effects of these adjustments on efficacy in patients with non-small-cell lung cancer remain unknown.

METHODS

We conducted a post hoc analysis of the PREDICT1 study (CJLSG1201), a multicenter prospective observational trial of carboplatin-pemetrexed. Glomerular filtration rate values in Calvert's formula were back-calculated from the administered dosages of carboplatin and the reported value of the target area under the curve. We estimated the serum creatinine adjustments and divided the patients into crude and adjusted groups.

RESULTS

Patients in the crude group (N = 169) demonstrated similar efficacy to those in the adjusted group (N = 104) in progression-free survival (PFS) and overall survival (OS) (hazard ratio [HR], 1.02; 95% confidence interval [CI], 0.76-1.35; p = 0.916 vs. HR, 0.87; 95% CI, 0.65-1.17; p = 0.363), with higher grade 3-4 hematologic toxicity. Among patients aged ≥75 years, the crude group (N = 47) showed superior efficacy compared with the adjusted group (N = 17) in PFS and OS (HR, 0.37; 95% CI, 0.20-0.69; p = 0.002 vs. HR, 0.43; 95% CI, 0.23-0.82; p = 0.010).

CONCLUSIONS

Serum creatinine adjustment may be associated with similar efficacy compared to the crude serum creatinine value. In older patients, the adjustment should be cautiously applied owing to the potential for reduced efficacy.

Trial watch: chemotherapy-induced immunogenic cell death in oncology

Immunogenic cell death (ICD) refers to an immunologically distinct process of regulated cell death that activates, rather than suppresses, innate and adaptive immune responses. Such responses culminate into T cell-driven immunity against antigens derived from dying cancer cells. The potency of ICD is dependent on the immunogenicity of dying cells as defined by the antigenicity of these cells and their ability to expose immunostimulatory molecules like damage-associated molecular patterns (DAMPs) and cytokines like type I interferons (IFNs). Moreover, it is crucial that the host's immune system can adequately detect the antigenicity and adjuvanticity of these dying cells. Over the years, several well-known chemotherapies have been validated as potent ICD inducers, including (but not limited to) anthracyclines, paclitaxels, and oxaliplatin. Such ICD-inducing chemotherapeutic drugs can serve as important combinatorial partners for anti-cancer immunotherapies against highly immuno-resistant tumors. In this Trial Watch, we describe current trends in the preclinical and clinical integration of ICD-inducing chemotherapy in the existing immuno-oncological paradigms.

COVID-19 vaccine incentive scheduling using an optimally controlled reinforcement learning model

We model Covid-19 vaccine uptake as a reinforcement learning dynamic between two populations: the vaccine adopters, and the vaccine hesitant. Using data available from the Center for Disease Control (CDC), we estimate the payoff matrix governing the interaction between these two groups over time and show they are playing a Hawk-Dove evolutionary game with an internal evolutionarily stable Nash equilibrium (the asymptotic percentage of vaccinated in the population). We then ask whether vaccine adoption can be improved by implementing dynamic incentive schedules that reward/punish the vaccine hesitant, and if so, what schedules are optimal and how effective are they likely to be? When is the optimal time to start an incentive program, how large should the incentives be, and is there a point of diminishing returns? By using a tailored replicator dynamic reinforcement learning model together with optimal control theory, we show that well designed and timed incentive programs can improve vaccine uptake by shifting the Nash equilibrium upward in large populations, but only so much, and incentive sizes above a certain threshold show diminishing returns.

How Surface-Enhanced Raman Spectroscopy Could Contribute to Medical Diagnoses

In the last decade, there has been a rapid increase in the number of surface-enhanced Raman scattering (SERS) spectroscopy applications in medical research. In this article we review some recent, and in our opinion, most interesting and promising applications of SERS spectroscopy in medical diagnostics, including those that permit multiplexing within the range important for clinical samples. We focus on the SERS-based detection of markers of various diseases (or those whose presence significantly increases the chance of developing a given disease), and on drug monitoring. We present selected examples of the SERS detection of particular fragments of DNA or RNA, or of bacteria, viruses, and disease-related proteins. We also describe a very promising and elegant ‘lab-on-chip’ approach used to carry out practical SERS measurements via a pad whose action is similar to that of a pregnancy test. The fundamental theoretical background of SERS spectroscopy, which should allow a better understanding of the operation of the sensors described, is also briefly outlined. We hope that this review article will be useful for researchers planning to enter this fascinating field.

Management of chemotherapy dose intensity for metastatic colorectal cancer (Review)

Chemotherapy dose intensity is a momentous parameter of antitumor clinical medication. In certain clinical trials, the actual application dose of the chemotherapeutic drugs is frequently different from the prescribed dose. The chemotherapy dose intensity completed in different trials is also variable, which has an impact on the treatment efficacy, disease prognosis and patient safety. When these agents are tested in the population, chemotherapy reduction and delay or failure to complete the planned cycle constantly occur due to age, performance status, adverse reactions and other reasons, resulting in the modification of the chemotherapy dose intensity. The present review analyzed the correlation between the chemotherapy dose intensity and the incidence of adverse reactions, the treatment efficacy and disease prognosis in clinical trials of metastatic colorectal cancer. Moreover, the clinical applications of chemotherapy dose intensity were discussed. Based on individual differences, the present review analyzed the clinical trials that examined the efficacy of the chemotherapy dose intensity in different patient populations. The conclusions suggested that different populations require a specific dose intensity to reduce treatment toxicity without affecting the curative effect.

High-grade glioma therapy: adding flexibility in trial design to improve patient outcomes

INTRODUCTION

Outcomes for patients with high grade gliomas have changed little over the past thirty years. This realization prompted renewed efforts to increase flexibility in the design and conduct of clinical brain tumor trials.

AREAS COVERED

This manuscript reviews the development of clinical trial methods, challenges and considerations of flexible clinical trial designs, approaches to improve identification and testing of active agents for high grade gliomas, and evaluation of their delivery to the central nervous system.

EXPERT OPINION

Flexibility can be introduced in clinical trials in several ways. Flexible designs tout smaller sample sizes, adaptive modifications, fewer control arms, and inclusion of multiple arms in one study. Unfortunately, modifications in study designs cannot address two challenges that are largely responsible for the lack of progress in treating high grade gliomas: 1) the identification of active pharmaceutical agents and 2) the delivery of these agents to brain tumor tissue in therapeutic concentrations. To improve the outcomes of patients with high grade gliomas efforts must be focused on the pre-clinical screening of drugs for activity, the ability of these agents to achieve therapeutic concentrations in non-enhancing tumors, and a willingness to introduce novel compounds in minimally pre-treated patient populations.

Therapeutic drug monitoring in oncology: International Association of Therapeutic Drug Monitoring and Clinical Toxicology consensus guidelines for imatinib therapy

Although therapeutic drug monitoring (TDM) is an important tool in guiding drug dosing for other areas of medicine including infectious diseases, cardiology, psychiatry and transplant medicine, it has not gained wide acceptance in oncology. For imatinib and other tyrosine kinase inhibitors, a flat dosing approach is utilised for management of oral chemotherapy. There are many published studies examining the correlation of blood concentrations with clinical effects of imatinib. The International Association of Therapeutic Drug Monitoring and Clinical Toxicology (IATDMCT) determined that there was a need to examine the published literature regarding utility of TDM in imatinib therapy and to develop consensus guidelines for TDM based on the available data. This article summarises the scientific evidence regarding TDM of imatinib, as well as the consensus guidelines developed by the IATDMCT.

Chemotherapeutic Stress Influences Epithelial-Mesenchymal Transition and Stemness in Cancer Stem Cells of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of estrogen and progesterone receptors (ER, PR) and lacking an overexpression of human epidermal growth factor receptor 2 (HER2). Apart from this lack of therapeutic targets, TNBC also shows an increased capacity for early metastasis and therapy resistance. Currently, many TNBC patients receive neoadjuvant chemotherapy (NACT) upon detection of the disease. With TNBC likely being driven at least in part by a cancer stem-like cell type, we wanted to evaluate the response of primary cancer stem cells (CSCs) to standard chemotherapeutics. Therefore, we set up a survival model using primary CSCs to mimic tumor cells in patients under chemotherapy. Breast cancer stem cells (BCSCs) were exposed to chemotherapeutics with a sublethal dose for six days. Surviving cells were allowed to recover in culture medium without chemotherapeutics. Surviving and recovered cells were examined in regard to proliferation, migratory capacity, sphere forming capacity, epithelial–mesenchymal transition (EMT) factor expression at the mRNA level, and cancer-related microRNA (miRNA) profile. Our results indicate that chemotherapeutic stress enhanced sphere forming capacity of BCSCs, and changed cell morphology and EMT-related gene expression at the mRNA level, whereas the migratory capacity was unaffected. Six miRNAs were identified as potential regulators in this process.

Susceptibility to adverse drug reactions

The pharmacological effects of a drug depend on its concentration at the site of action, and therefore on the concentration in blood and on the dose. The relationship between the concentration or dose and the corresponding effect can usually be represented mathematically as a rectangular hyperbola; when effect is plotted against log concentration or log dose, the curve is sigmoidal. Inevitably, the effect size and the doses causing benefit and harm will differ among individuals, since they are biological phenomena: some individuals are more likely than others to suffer harm at any given dose. Some harmful effects can occur at much lower doses than those used in therapeutics; that is, the log dose-response curve for harm lies far to the left of the log dose-response curve for benefit. Those who suffer such reactions are hypersusceptible. When the dose-response curves for harm and therapeutic effect are in the same range, dose cannot separate the harmful effects from the therapeutic effects, and adverse reactions are collateral. Toxic effects occur when harmful doses are above the doses needed for benefit. In this review we consider factors that influence a subject's susceptibility to adverse drug reactions. Determinants of susceptibility include Immunological, Genetic, demographic (Age and Sex), Physiological and Exogenous factors (drug-drug interactions, for example), and Diseases and disorders such as renal failure, giving the mnemonic I GASPED. Some susceptibility factors are discrete (for example, all-or-none) and some are continuous; susceptibility can therefore be discrete or continuous; and the factors can interact to determine a person's overall susceptibility to harm.

The rationale of dose-response curves in selecting cancer drug dosing

Drug development for cancer chemotherapy has an interesting history. A mix of serendipity, animal, cell line, and standard pharmacological principles of dose, dose-response, dose-concentration, dose intensity and combination therapies have been used to develop optimal dosing schedules. However in practice, significant gaps in the translation of preclinical to clinical dosing schedules persist, and clinical development has instead moved to new drug development. A older chemotherapies are still the backbone of most solid tumour schedules, therapeutic drug monitoring has emerged as a method for optimising the dose for individual patients.