Design of experiment in drug development: optimal allocations in multi-arm clinical trials and design space for multi-step processes

In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.

Metabolomics and its potential in drug development

Metabolomics is the global and unbiased survey of the complement of small molecules (say, <1 kDa) in a biofluid, tissue, organ or organism and measures the end-products of the cellular metabolism of both endogenous and exogenous substrates. Many drug candidates fail during Phase II and III clinical trials at an enormous cost to the pharmaceutical industry in terms of both time lost and of financial resources. The constantly evolving model of drug development now dictates that biomarkers should be employed in preclinical development for the early detection of likely-to-fail candidates. Biomarkers may also be useful in the preselection of patients and through the subclassification of diseases in clinical drug development. Here we show with examples how metabolomics can assist in the preclinical development phases of discovery, pharmacology, toxicology, and ADME. Although not yet established as a clinical trial patient prescreening procedure, metabolomics shows considerable promise in this regard. We can be certain that metabolomics will join genomics and transcriptomics in lubricating the wheels of clinical drug development in the near future.

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

Interpreting adverse signals in diabetes drug development programs

Detection and interpretation of adverse signals during preclinical and clinical stages of drug development inform the benefit-risk assessment that determines suitability for use in real-world situations. This review considers some recent signals associated with diabetes therapies, illustrating the difficulties in ascribing causality and evaluating absolute risk, predictability, prevention, and containment. Individual clinical trials are necessarily restricted for patient selection, number, and duration; they can introduce allocation and ascertainment bias and they often rely on biomarkers to estimate long-term clinical outcomes. In diabetes, the risk perspective is inevitably confounded by emergent comorbid conditions and potential interactions that limit therapeutic choice, hence the need for new therapies and better use of existing therapies to address the consequences of protracted glucotoxicity. However, for some therapies, the adverse effects may take several years to emerge, and it is evident that faint initial signals under trial conditions cannot be expected to foretell all eventualities. Thus, as information and experience accumulate with time, it should be accepted that benefit-risk deliberations will be refined, and adjustments to prescribing indications may become appropriate. © 2013 by the American Diabetes Association.

Cheaper Faster Drug Development Validated By The Repositioning Of Drugs Against Neglected Tropical Diseases.

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

The role of molecular imaging in modern drug development

Drug development represents a highly complex, inefficient and costly process. Over the past decade, the widespread use of nuclear imaging, owing to its functional and molecular nature, has proven to be a determinant in improving the efficiency in selecting the candidate drugs that should either be abandoned or moved forward into clinical trials. This helps not only with the development of safer and effective drugs but also with the shortening of time-to-market. The modern concept and future trends concerning molecular imaging will assumedly be hybrid or multimodality imaging, including combinations between high sensitivity and functional (molecular) modalities with high spatial resolution and morphological techniques.

Propolis: A complex natural product with a plethora of biological activities that can be explored for drug development

The health industry has always used natural products as a rich, promising, and alternative source of drugs that are used in the health system. Propolis, a natural resinous product known for centuries, is a complex product obtained by honey bees from substances collected from parts of different plants, buds, and exudates in different geographic areas. Propolis has been attracting scientific attention since it has many biological and pharmacological properties, which are related to its chemical composition. Several in vitro and in vivo studies have been performed to characterize and understand the diverse bioactivities of propolis and its isolated compounds, as well as to evaluate and validate its potential. Yet, there is a lack of information concerning clinical effectiveness. The goal of this review is to discuss the potential of propolis for the development of new drugs by presenting published data concerning the chemical composition and the biological properties of this natural compound from different geographic origins.

Novel approaches in anti-arenaviral drug development.

Hemorrhagic fevers caused by arenaviruses are among the most devastating emerging human diseases. Considering the number of individuals affected, the current lack of a licensed vaccine, and the limited therapeutic options, arenaviruses are arguably among the most neglected tropical pathogens and the development of efficacious anti-arenaviral drugs is of high priority. Over the past years significant efforts have been undertaken to identify novel potent inhibitors of arenavirus infection. High throughput screening of small molecule libraries employing pseudotype platforms led to the discovery of several potent and broadly active inhibitors of arenavirus cell entry that are effective against the major hemorrhagic arenaviruses. Mechanistic studies revealed that these novel entry inhibitors block arenavirus membrane fusion and provided novel insights into the unusual mechanism of this process. The success of these approaches highlights the power of small molecule screens in antiviral drug discovery and establishes arenavirus membrane fusion as a robust drug target. These broad screenings have been complemented by strategies targeting cellular factors involved in productive arenavirus infection. Approaches targeting the cellular protease implicated in maturation of the fusion-active viral envelope glycoprotein identified the proteolytic processing of the arenavirus glycoprotein precursor as a novel and promising target for anti-arenaviral strategies.

Ergosterol biosynthesis and drug development for Chagas disease

This article presents an overview of the currently available drugs nifurtimox (NFX) and benznidazole (BZN) used against Trypanosoma cruzi, the aetiological agent of Chagas disease; herein we discuss their limitations along with potential alternatives with a focus on ergosterol biosynthesis inhibitors (EBI). These compounds are currently the most advanced candidates for new anti-T. cruzi agents given that they block de novo production of 24-alkyl-sterols, which are essential for parasite survival and cannot be replaced by a host's own cholesterol. Among these compounds, new triazole derivatives that inhibit the parasite's C14± sterol demethylase are the most promising, as they have been shown to have curative activity in murine models of acute and chronic Chagas disease and are active against NFX and BZN-resistant T. cruzi strains; among this class of compounds, posaconazole (Schering-Plough Research Institute) and ravuconazole (Eisai Company) are poised for clinical trials in Chagas disease patients in the short term. Other T. cruzi-specific EBI, with in vitro and in vivo potency, include squalene synthase, lanosterol synthase and squalene epoxidase-inhibitors as well as compounds with dual mechanisms of action (ergosterol biosynthesis inhibition and free radical generation), but they are less advanced in their development process. The main putative advantages of EBI over currently available therapies include their higher potency and selectivity in both acute and chronic infections, activity against NFX and BZN-resistant T. cruzi strains, and much better tolerability and safety profiles. Limitations may include complexity and cost of manufacture of the new compounds. As for any new drug, such compounds will require extensive clinical testing before being introduced for clinical use, and the complexity of such studies, particularly in chronic patients, will be compounded by the current limitations in the verification of true parasitological cures for T. cruzi infections.

Optimising translational oncology in clinical practice: Strategies to accelerate progress in drug development.

Despite intense efforts, the socioeconomic burden of cancer remains unacceptably high and treatment advances for many common cancers have been limited, suggesting a need for a new approach to drug development. One issue central to this lack of progress is the heterogeneity and genetic complexity of many tumours. This results in considerable variability in therapeutic response and requires knowledge of the molecular profile of the tumour to guide appropriate treatment selection for individual patients. While recent advances in the molecular characterisation of different cancer types have the potential to transform cancer treatment through precision medicine, such an approach presents a major economic challenge for drug development, since novel targeted agents may only be suitable for a small cohort of patients. Identifying the patients who would benefit from individual therapies and recruiting sufficient numbers of patients with particular cancer subtypes into clinical trials is challenging, and will require collaborative efforts from research groups and industry in order to accelerate progress. A number of molecular screening platforms have already been initiated across Europe, and it is hoped that these networks, along with future collaborations, will benefit not only patients but also society through cost reductions as a result of more efficient use of resources. This review discusses how current developments in translational oncology may be applied in clinical practice in the future, assesses current programmes for the molecular characterisation of cancer and describes possible collaborative approaches designed to maximise the benefits of translational science for patients with cancer.

Brain metastasis: opportunity for drug development?

PURPOSE OF REVIEW: Brain metastases are a common clinical problem, and only limited treatment options exist. We review recent advances in medical brain metastasis research with a focus on the most common tumor types associated with secondary brain colonization: melanoma, breast cancer and lung cancer. We speculate on opportunities for drug development in patients with brain metastases, both as a treatment of established disease and as an adjuvant and prophylactic strategy. RECENT FINDINGS: BRAF inhibitors and the immunomodulatory anticytotoxic T-lymphocyte-associated antigen 4 antibody ipilimumab have shown clinically meaningful activity in melanoma patients with brain metastases. In breast cancer, current studies on drug treatment of brain metastases are mainly focusing on human epidermal growth factor receptor 2 targeting agents such as lapatinib. Emerging data seem to implicate a potential role of targeted agents including antiangiogenic compounds, pazopanib, and epithelial growth factor receptor inhibitors for prevention of brain metastasis formation in breast cancer or nonsmall cell lung cancer. SUMMARY: Novel drugs are beginning to enter clinical practice for selected patients with brain metastases. The promising findings from recent studies may fuel more research on brain metastases and their optimal drug treatment.

Research Ethics and Commercial Drug Development: When Integrity Threatens Profitability

Étude de cas / Case study

Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug-development programme

Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.

CDK9 a potential target for drug development

The family of Cyclin-Dependent Kinases (CDKs) can be subdivided into two major functional groups based on their roles in cell cycle and/or transcriptional control. CDK9 is the catalytic subunit of positive transcription elongation factor b (P-TEFb). CDK9 is the kinase of the TAK complex (Tat-associated kinase complex), and binds to Tat protein of HIV, suggesting a possible role for CDK9 in AIDS progression. CDK9 complexed with its regulatory partner cyclin T1, serves as a cellular mediator of the transactivation function of the HIV Tat protein. P-TEFb is responsible for the phosphorylation of the carboxyl-terminal domain of RNA Pol II, resulting in stimulation of transcription. Furthermore, the complexes containing CDK9 induce the differentiation in distinct tissue. The CDK9/cyclin T1 complex is expressed at higher level in more differentiated primary neuroectodermal and neuroblastoma tumors, showing a correlation between the kinase expression and tumor differentiation grade. This may have clinical and therapeutical implications for these tumor types. Among the CDK inhibitors two have shown to be effective against CDK9: Roscovitine and Flavopiridol. These two inhibitors prevented the replication of human immunodeficiency virus (HIV) type 1 by blocking Tat transactivation of the HIV type 1 promoter. These compounds inhibit CDKs by binding to the catalytic domain in place of ATP, preventing transfer of a phosphate group to the substrate. More sensitive therapeutic agents of CDK9 can be designed, and structural studies can add information in the understanding of this kinase. The major features related to CDK9 inhibition will be reviewed in this article.