Evolution of Resistance to Targeted Anti-Cancer Therapies during Continuous and Pulsed Administration Strategies

The discovery of small molecules targeted to specific oncogenic pathways has revolutionized anti-cancer therapy. However, such therapy often fails due to the evolution of acquired resistance. One long-standing question in clinical cancer research is the identification of optimum therapeutic administration strategies so that the risk of resistance is minimized. In this paper, we investigate optimal drug dosing schedules to prevent, or at least delay, the emergence of resistance. We design and analyze a stochastic mathematical model describing the evolutionary dynamics of a tumor cell population during therapy. We consider drug resistance emerging due to a single (epi)genetic alteration and calculate the probability of resistance arising during specific dosing strategies. We then optimize treatment protocols such that the risk of resistance is minimal while considering drug toxicity and side effects as constraints. Our methodology can be used to identify optimum drug administration schedules to avoid resistance conferred by one (epi)genetic alteration for any cancer and treatment type.     

Pharmacological and Host Considerations Surrounding Dose Selection and Duration of Therapy with Echinocandins

Caspofungin, micafungin and anidulafungin are antifungal drugs with excellent safety profiles. Dosing regimens and treatment durations must be appropriate for optimal patient outcomes. Overall, factors that affect dosing of all three drugs are similar. Drug-specific properties, including in vitro concentration-dependent antifungal activity, activity against fungal biofilms, and pharmacokinetic and pharmacodynamic parameters influence dose selection and duration of therapy. Dosing strategies that provide “unbound” plasma drug concentrations exceeding the minimum inhibitory concentration (or minimum effective concentration) of the fungus are essential. Patient weight, age and illness severity are also important considerations for adequate exposure to drug: individuals >66 kg, pediatric patients and the critically-ill clear drug at higher rates although drug product information guidelines do not recommend for these populations to receive doses higher than those currently used. Clinical studies of treatment of, and prophylaxis against, Candida and Aspergillus infection indicate that currently recommended dosing regimens are adequate in most instances.     

Evolution of resistance to anti-cancer therapy during general dosing schedules

Anti-cancer drugs targeted to specific oncogenic pathways have shown promising therapeutic results in the past few years; however, drug resistance remains an important obstacle for these therapies. Resistance to these drugs can emerge due to a variety of reasons including genetic or epigenetic changes which alter the binding site of the drug target, cellular metabolism or export mechanisms. Obtaining a better understanding of the evolution of resistant populations during therapy may enable the design of more effective therapeutic regimens which prevent or delay progression of disease due to resistance. In this paper, we use stochastic mathematical models to study the evolutionary dynamics of resistance under time-varying dosing schedules and pharmacokinetic effects. The populations of sensitive and resistant cells are modeled as multi-type non-homogeneous birth-death processes in which the drug concentration affects the birth and death rates of both the sensitive and resistant cell populations in continuous time. This flexible model allows us to consider the effects of generalized treatment strategies as well as detailed pharmacokinetic phenomena such as drug elimination and accumulation over multiple doses. We develop estimates for the probability of developing resistance and moments of the size of the resistant cell population. With these estimates, we optimize treatment schedules over a subspace of tolerated schedules to minimize the risk of disease progression due to resistance as well as locate ideal schedules for controlling the population size of resistant clones in situations where resistance is inevitable. Our methodology can be used to describe dynamics of resistance arising due to a single (epi)genetic alteration in any tumor type.     

A multi-type branching model with varying environment for bacterial dynamics with postantibiotic effect

A multi-type branching process with varying environment was used to construct a pharmacokinetic/pharmacodynamic (PK/PD) model that captures the postantibiotic effect (PAE) seen in bacterial populations after exposure of antibiotics. This phenomenon of continued inhibition of bacterial growth even after removal of the antibiotic from the growth medium is of high relevance in the context of optimizing dosing regimens. The clinical implication of long PAEs lies in the interesting possibility of increasing the intervals between drug administrations.The model structure is generalizable to most types of antibiotics and is useful both as a theoretical framework for understanding the time properties of PAE and to explore optimal antibiotic dosing regimens. Data from an in vitro study with Escherichia coli exposed to different dosing regimens of cefotaxime were used to evaluate the model.     

Antimalarials for children with Plasmodium vivax infection: Current status,challenges, and research priorities

The aim of this narrative review is to summarise efficacy and pharmacokinetic data for Plasmodium vivax in children. The burden of P. vivax malaria in children continues to remain a significant public health issue, and the need for improved treatment regimens for this vulnerable population is critical. Relapse after re-activation of dormant liver-stage hypnozoites poses additional challenges for treatment, elimination, and control strategies for P. vivax. Whilst it is recognised that paediatric pharmacology may be significantly influenced by anatomical and physiological changes of childhood, dosing regimens often continue to be extrapolated from adult data, highlighting the need for antimalarial dosing in children to be evaluated in early phase clinical trials. This will ensure that globally recommended treatment regimens do not result in suboptimal dosing in children. Furthermore, the development of affordable paediatric formulations to enhance treatment acceptability and widespread G6PD testing to facilitate use of anti-hypnozoite treatment such as primaquine and tafenoquine, should be further prioritised. As the world prepares for malaria elimination, a renewed focus on P. vivax malaria provides an ideal opportunity to harness momentum and ensure that all populations, including children have access to safe, efficacious, and correctly dosed antimalarial therapies.     

Pharmacodynamics of antifungal drugs: A strategy to optimize efficacy

Pharmacodynamic studies examine the relationship between drug pharmacokinetics and outcome. These investigations have been shown to be helpful for the design of dosing intervals, choice of optimal dose levels, and the development of susceptibility breakpoints. Pharmacodynamic studies with available antifungal agents have been useful in developing optimal dosing regimens to improve efficacy and reduce treatment-associated toxicities. This review summarizes accepted antifungal concepts and discusses recent advances in the field.     

The combination of population pharmacokinetic studies

Pharmacokinetic data consist of drug concentrations with associated known sampling times and are collected following the administration of known dosage regimens. Population pharmacokinetic data consist of such data on a number of individuals, possibly along with individual-specific characteristics. During drug development, a number of population pharmacokinetic studies are typically carried out and the combination of such studies is of great importance for characterizing the drug and, in particular, for the design of future studies. In this paper, we describe a model that may be used to combine population pharmacokinetic data. The model is illustrated using six phase I studies of the antiasthmatic drug fluticasone propionate. Our approach is Bayesian and computation is carried out using Markov chain Monte Carlo. We provide a number of simplifications to the model that may be made in order to ease simulation from the posterior distribution.     

Targeted drug delivery by gemtuzumab ozogamicin: mechanism-based mathematical model for treatment strategy improvement and therapy individualization

Gemtuzumab ozogamicin (GO) is a chemotherapy-conjugated anti-CD33 monoclonal antibody effective in some patients with acute myeloid leukemia (AML). The optimal treatment schedule and optimal timing of GO administration relative to other agents remains unknown. Conventional pharmacokinetic analysis has been of limited insight for the schedule optimization. We developed a mechanism-based mathematical model and employed it to analyze the time-course of free and GO-bound CD33 molecules on the lekemic blasts in individual AML patients treated with GO. We calculated expected intravascular drug exposure (I-AUC) as a surrogate marker for the response to the drug. A high CD33 production rate and low drug efflux were the most important determinants of high I-AUC, characterizing patients with favorable pharmacokinetic profile and, hence, improved response. I-AUC was insensitive to other studied parameters within biologically relevant ranges, including internalization rate and dissociation constant. Our computations suggested that even moderate blast burden reduction prior to drug administration enables lowering of GO doses without significantly compromising intracellular drug exposure. These findings indicate that GO may optimally be used after cyto-reductive chemotherapy, rather than before, or concomitantly with it, and that GO efficacy can be maintained by dose reduction to 6 mg/m(2) and a dosing interval of 7 days. Model predictions are validated by comparison with the results of EORTC-GIMEMA AML19 clinical trial, where two different GO schedules were administered. We suggest that incorporation of our results in clinical practice can serve identification of the subpopulation of elderly patients who can benefit most of the GO treatment and enable return of the currently suspended drug to clinic.     

Antifungal Dose Adjustment in Renal and Hepatic Dysfunction: Pharmacokinetic and Pharmacodynamic Considerations

Adjusting the dose of antifungal agents for renal and hepatic impairment can be challenging given that clinicians must rely on limited pharmacokinetic data to derive specific regimens. These pharmacokinetic studies are typically performed in a small number of patients without invasive fungal infection, and results are not often reported in concert with accepted pharmacodynamic indices. This article aims to review pertinent pharmacokinetic studies of antifungal drugs in patients with renal or hepatic dysfunction. The impact of novel continuous renal replacement therapy techniques on the pharmacokinetic disposition of antifungal agents will also be described where data are available. Subsequently, this review provides recommendations for antifungal drug dosing in patients with kidney or liver dysfunction after accounting for established or emerging pharmacokinetic-pharmacodynamic relationships as they relate to antifungal drug efficacy in vivo.     

Pharmacogenetics in drug regulation: promise, potential and pitfalls

Pharmacogenetic factors operate at pharmacokinetic as well as pharmacodynamic levels-the two components of the dose-response curve of a drug. Polymorphisms in drug metabolizing enzymes, transporters and/or pharmacological targets of drugs may profoundly influence the dose-response relationship between individuals. For some drugs, although retrospective data from case studies suggests that these polymorphisms are frequently associated with adverse drug reactions or failure of efficacy, the clinical utility of such data remains unproven. There is, therefore, an urgent need for prospective data to determine whether pre-treatment genotyping can improve therapy. Various regulatory guidelines already recommend exploration of the role of genetic factors when investigating a drug for its pharmacokinetics, pharmacodynamics, dose-response relationship and drug interaction potential. Arising from the global heterogeneity in the frequency of variant alleles, regulatory guidelines also require the sponsors to provide additional information, usually pharmacogenetic bridging data, to determine whether data from one ethnic population can be extrapolated to another. At present, sponsors explore pharmacogenetic influences in early clinical pharmacokinetic studies but rarely do they carry the findings forward when designing dose-response studies or pivotal studies. When appropriate, regulatory authorities include genotype-specific recommendations in the prescribing information. Sometimes, this may include the need to adjust a dose in some genotypes under specific circumstances. Detailed references to pharmacogenetics in prescribing information and pharmacogenetically based prescribing in routine therapeutics will require robust prospective data from well-designed studies. With greater integration of pharmacogenetics in drug development, regulatory authorities expect to receive more detailed genetic data. This is likely to complicate the drug evaluation process as well as result in complex prescribing information. Genotype-specific dosing regimens will have to be more precise and marketing strategies more prudent. However, not all variations in drug responses are related to pharmacogenetic polymorphisms. Drug response can be modulated by a number of non-genetic factors, especially co-medications and presence of concurrent diseases. Inappropriate prescribing frequently compounds the complexity introduced by these two important non-genetic factors. Unless prescribers adhere to the prescribing information, much of the benefits of pharmacogenetics will be squandered. Discovering highly predictive genotype-phenotype associations during drug development and demonstrating their clinical validity and utility in well-designed prospective clinical trials will no doubt better define the role of pharmacogenetics in future clinical practice. In the meantime, prescribing should comply with the information provided while pharmacogenetic research is deservedly supported by all concerned but without unrealistic expectations.     

Animal models in the pharmacokinetic/pharmacodynamic evaluation of antimicrobial agents

Animal infection models in the pharmacokinetic/pharmacodynamic (PK/PD) evaluation of antimicrobial therapy serve an important role in preclinical assessments of new antibiotics, dosing optimization for those that are clinically approved, and setting or confirming susceptibility breakpoints. The goal of animal model studies is to mimic the infectious diseases seen in humans to allow for robust PK/PD studies to find the optimal drug exposures that lead to therapeutic success. The PK/PD index and target drug exposures obtained in validated animal infection models are critical components in optimizing dosing regimen design in order to maximize efficacy while minimize the cost and duration of clinical trials. This review outlines the key components in animal infection models which have been used extensively in antibiotic discovery and development including PK/PD analyses.     

Costs versus benefits: best possible and best practical treatment regimens for HIV

Current HIV therapy, although highly effective, may cause very serious side effects, making adherence to the prescribed regimen difficult. Mathematical modeling may be used to evaluate alternative treatment regimens by weighing the positive results of treatment, such as higher levels of helper T cells, against the negative consequences, such as side effects and the possibility of resistance mutations. Although estimating the weights assigned to these factors is difficult, current clinical practice offers insight by defining situations in which therapy is considered “worthwhile”. We therefore use clinical practice, along with the probability that a drug-resistant mutation is present at the start of therapy, to suggest methods of rationally estimating these weights. In our underlying model, we use ordinary differential equations to describe the time course of in-host HIV infection, and include populations of both activated CD4⁺ T cells and CD8⁺ T cells. We then determine the best possible treatment regimen, assuming that the effectiveness of the drug can be continually adjusted, and the best practical treatment regimen, evaluating all patterns of a block of days “on” therapy followed by a block of days “off” therapy. We find that when the tolerance for drug-resistant mutations is low, high drug concentrations which maintain low infected cell populations are optimal. In contrast, if the tolerance for drug-resistant mutations is fairly high, the optimal treatment involves periods of reduced drug exposure which consequently boost the immune response through increased antigen exposure. We elucidate the dependence of the optimal treatment regimen on the pharmacokinetic parameters of specific antiviral agents.     

Prediction of clinical responses in a simulated phase III trial of Crohn's patients administered the antisense phosphorothioate oligonucleotide ISIS 2302: comparison of proposed dosing regimens

ISIS 2302, an antisense phosphorothioate oligonucleotide (ODN) targeting human intercellular adhesion molecule-1 (ICAM-1) mRNA, is currently being evaluated for treatment of patients with Crohn's disease. From data collected in phase II clinical studies with ISIS 2302, validated population pharmacokinetic and exposure-response models were developed and used to simulate the plasma exposure and clinical response results for a proposed phase III trial design involving 100 patients treated with active drug and 50 patients treated with placebo. Simulated results of 1000 replications of the trial were calculated for various proposed dosing regimens. Overall, the simulated results indicated that a fixed dose regimen (250-400 mg, depending on patient sex and total body weight) given three times weekly provides both desirable ISIS 2302 plasma exposure and a high rate of clinical response in this patient population. However, the simulated results also suggest that inclusion of a larger number of patients than projected may be necessary to provide a desirable probability of study success (i.e., >80%), regarding demonstration of statistically significant differences between the active treatment and placebo groups for the primary clinical response measure (CCR rate).     

Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients

Background

The advent of targeted therapy for cancer treatment has brought about a paradigm shift in the clinical management of human malignancies. Agents such as erlotinib used for EGFR-mutant non-small cell lung cancer or imatinib for chronic myeloid leukemia, for instance, lead to rapid tumor responses. Unfortunately, however, resistance often emerges and renders these agents ineffective after a variable amount of time. The FDA-approved dosing schedules for these drugs were not designed to optimally prevent the emergence of resistance. To this end, we have previously utilized evolutionary mathematical modeling of treatment responses to elucidate the dosing schedules best able to prevent or delay the onset of resistance. Here we expand on our approaches by taking into account dose-dependent mutation rates at which resistant cells emerge. The relationship between the serum drug concentration and the rate at which resistance mutations arise can lead to non-intuitive results about the best dose administration strategies to prevent or delay the emergence of resistance.

Methods

We used mathematical modeling, available clinical trial data, and different considerations of the relationship between mutation rate and drug concentration to predict the effectiveness of different dosing strategies.

Results

We designed several distinct measures to interrogate the effects of different treatment dosing strategies and found that a low-dose continuous strategy coupled with high-dose pulses leads to the maximal delay until clinically observable resistance. Furthermore, the response to treatment is robust against different assumptions of the mutation rate as a function of drug concentration.

Conclusions

For new and existing targeted drugs, our methodology can be employed to compare the effectiveness of different dose administration schedules and investigate the influence of changing mutation rates on outcomes.     

A theoretical analysis of interval drug dosing for cell-cycle-phase-specific drugs.

A formal method is provided for predicting the effect on treatment efficacy of cell-cycle-phase-specific drugs, such as the AIDS drug zidovudine (AZT) or the cancer drug cytosine arabinoside (ara-C). Our analysis shows that the elimination of somatic cells or viruses depends not only on the drug's pharmacokinetic and pharmacodynamic properties, but also the duration of the dosing interval per se and on the life-cycle parameters, that is, the duration of the drug-susceptible life phase, the duration of the whole life cycle, and the proliferation rate. The results support those of simplified models in showing that drug toxicity to the host may be minimized when the dosing interval is an integer multiple of the average cycle time of the host susceptible cells. This prediction has been verified in mice treated with AZT or ara-C.     

The effect of heterogeneity on optimal regimens in cancer chemotherapy

Optimal drug regimens for cancer chemotherapy are determined when knowledge is only available on the behaviour of the tumour and the drugs used, over a population of patients. The case of two drugs is investigated where they are equivalent on average. Our calculations indicate that the optimal regimen has both drugs given initially but then sequences the two drugs. Our calculations also indicate that as tumour heterogeneity increases, the benefit to be gained from the optimal regimen can decrease in comparison to reasonable regimens. This has the effect of complicating the calculation of optimal regimens in a clinical setting, and may explain why results in experimental oncology fail to carry over to clinical oncology.     

Correlation of in vitro and in vivo resistance development to antimicrobial agents

Preclinical in vitro and in vivo determinations of the likelihood of an antibiotic to develop resistance can and has proven predictive of their likelihood of resistance development in patients. Problematic antibiotic/bacterial species combinations are often associated with high frequencies of single-step resistance development in that species. Thus, treatment of organisms with rapid in vitro emergence of drug resistance should be monitored carefully. In vitro studies, however, are limited in predicting resistance mediated through acquisition of a resistance plasmid.The frequency of resistance development to a drug is dependent on factors such as the drug used for selections, the concentration (i.e., dosing) of the drug, the bacterium, and the site of infection. Organisms intrinsically less susceptible to an antibiotic develop resistance rapidly due to their low therapeutic ratios. Since cross-resistance often occurs within an antibiotic class, it may be desirable to initiate therapy with a drug with low resistance-selecting potential. Optimal dosing regimens are especially critical when treating bacterial species likely to develop drug resistance. Though combination drug therapies have proven affective in experimental animal infections and in man, they do not prevent resistant variants from emerging. Understanding of drug-resistance development will contribute to our management of infectious diseases.     

HIV drug resistance and optimization of antiviral treatment in resource-poor countries

HIV drug resistance has been associated with treatment failure in Western countries but the lessons learned can be useful in optimization of highly active antiretroviral treatment (HAART) in resource-poor settings. There is a need to improve access to HAART in such regions, but appropriate strategies must be rapidly implemented, such as adapted programs to facilitate adherence to therapy, rational use of genotypic drug resistance monitoring in specific situations, and use of alternative treatment regimens. The implications of HIV genetic diversity must also be considered in management of drug resistance.     

Pharmacokinetic conversion study of a new cyclosporine formulation in stable adult renal transplant recipients

Cyclosporine A (CyA) is a standard component of immunosuppressive regimens. It is a critical-dose drug for which a minor change in absorption can have important clinical consequences. The aim of the study was to compare the pharmacokinetics and safety of the new generic CyA formulation, Equoral capsules, after a switch from original formulation, Neoral capsules, in seventy stable adult renal transplant recipients. The extent and rate of pharmacokinetic parameters for bioequivalence were compared in a non-randomized, steady-state clinical study with fixed non-replicate study design. Pharmacokinetic analysis of CyA have shown that both the rate and extent of absorption of Equoral does not differ significantly from that of Neoral. At identical dosing, the new formulation was found to have geometric means of C(max) 717 ng/ml and AUCtau 3108 ng/ml.h, while corresponding results of comparator were 725 ng/ml and AUCtau 3039 ng/ml.h, respectively. The 90 % confidence intervals of C(max) and AUCtau were within 80- 125 % interval of the mean values. The results suggest that Equoral capsules can be used as an alternative treatment to Neoral capsules in CyA regimen.