Streamline Drug Development Research Articles

Establishing virtual bioequivalence and clinically relevant specifications using in vitro biorelevant dissolution testing and physiologically-based population pharmacokinetic modeling. case example: Naproxen

BackgroundPhysiologically-based population pharmacokinetic modeling (popPBPK) coupled with in vitro biopharmaceutics tools such as biorelevant dissolution testing can serve as a powerful tool to establish virtual bioequivalence and set clinically relevant specifications. One of several applications of popPBPK modeling is in the emerging field of virtual bioequivalence (VBE), where it can be used to streamline drug development by implementing model-informed formulation design and to inform regulatory decision-making e.g., with respect to evaluating the possibility of extending BCS-based biowaivers beyond BCS Class I and III compounds in certain cases. MethodsIn this study, Naproxen, a BCS class II weak acid was chosen as the model compound. In vitro biorelevant solubility and dissolution experiments were performed and the resulting data were used as an input to the PBPK model, following a stepwise workflow for the confirmation of the biopharmaceutical parameters. The naproxen PBPK model was developed by implementing a middle-out approach and verified against clinical data obtained from the literature. Once confidence in the performance of the model was achieved, several in vivo dissolution scenarios, based on model-based analysis of the in vitro data, were used to simulate clinical trials in healthy adults. Inter-occasion variability (IOV) was also added to critical physiological parameters and mechanistically propagated through the simulations. The various trials were simulated on a “worst/best case” dissolution scenario and average bioequivalence was assessed according to Cmax, AUC and Tmax. ResultsVBE results demonstrated that naproxen products with in vitro dissolution reaching 85% dissolved within 90 min would lie comfortably within the bioequivalence limits for Cmax and AUC. Based on the establishment of VBE, a dissolution “safe space” was designed and a clinically relevant specification for naproxen products was proposed. The interplay between formulation-related and drug-specific PK parameters (e.g., t1/2) to predict the in vivo performance was also investigated. ConclusionOver a wide range of values, the in vitro dissolution rate is not critical for the clinical performance of naproxen products and therefore naproxen could be eligible for BCS-based biowaivers based on in vitro dissolution under intestinal conditions. This approach may also be applicable to other poorly soluble acidic compounds with long half-lives, providing an opportunity to streamline drug development and regulatory decision-making without putting the patient at a risk.

Methods for fabrication and evaluation of a 3D microengineered model of myelinated peripheral nerve

Objective. The cost and low success rates of the neurological drug development pipeline have diverted the pharmaceutical industry to ‘nerve-on-a-chip’ systems as preclinical models to streamline drug development. We present a novel micro-engineered 3D hydrogel platform for the culture of myelinated embryonic peripheral neural tissue to serve as an effective in vitro model for electrophysiological and histological analysis that could be adopted for preclinical testing. Approach. Dorsal root ganglions (DRG) from 15 d old embryonic rats were cultured in 3D hydrogel platforms. The interaction between Schwann cells (SC) and neurons during axonal development and regeneration affects the direction of growth and the synthesis of myelin sheaths. Induction of myelination was performed with two approaches: the addition of exogenous SC and promoting migration of endogenous SC. Main results. Histological analysis of the preparation utilizing exogenous SC showed aligned, highly fasciculated axonal growth with noticeable myelin sheaths around axons. Separately, electrophysiological testing of the preparation utilizing endogenous SC showed increased amplitude of the compound action potential and nerve conduction velocity in the presence of ascorbic acid (AA). Significance. This platform has immense potential to be a useful and translatable in vitro testing tool for drug discovery and myelination studies.

Decoding the Pathway to Biomarker Qualification: Will an Evidentiary Map Framework Do the Trick?

Drug development is a costly and time-consuming endeavor with high potential risks. These and other barriers could discourage pharmaceutical companies from pursuing novel drug development. Concerns have arisen periodically about the flattening or decreasing rates of new drug approvals and applications filed at the U.S. Food and Drug Administration (FDA). Leveraging the use of biomarkers represents a viable alternative to streamline drug development. A biomarker is “a defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions.” (1) Biomarkers are vital for drug development, with potential safety (e.g., early identification of drug toxicity) and efficacy (e.g., response to therapy, end-point measures) benefits. Therefore, stakeholders are committed to developing pathways for effective biomarker qualification. Biomarker qualification …

Early Phase Clinical Trial Designs – State of Play and Adapting for the Future

The process of anti-cancer drug development is complex, with high attrition rates. Factors that may optimise this process include well-constructed and relevant pre-clinical testing and use of biomarkers for patient selection. However, the design of early phase clinical trials will probably play a vital role in both the robust clinical investigation of new targeted therapies and in streamlining drug development. In this overview, we assess current concepts in phase I clinical trials, highlighting issues and opportunities to improve their meaningfulness. The particular challenge of how to design combination trials is addressed, with focus on the potential of new adaptive and model-based designs.

THE COALITION AGAINST MAJOR DISEASES: TOWARD U.S. FDA QUALIFICATION OF HIPPOCAMPAL VOLUME AS A BIOMARKER FOR ENRICHMENT IN CLINICAL TRIALS FOR PRE-DEMENTIA STAGES OF ALZHEIMER'S DISEASE

The development of therapeutic agents for pre-dementia stages of Alzheimer's disease (AD) poses the challenge of selecting homogeneous cohorts of individuals for clinical trials. Trial enrichment via prognostic biomarkers provides one means of doing so. In pre-dementia patients, hippocampal atrophy is associated with progression to dementia. CAMD is pursuing regulatory qualification of baseline intracranial volume-adjusted hippocampal volume (ICV-HV) as an enrichment biomarker in pre-dementia trials, supported by a model-based analysis, through the development of a quantitative description of disease progression. To assess the utility of ICV-HV as a prognostic biomarker for clinical trial enrichment, patient-level data from three sources – the Alzheimer's Disease Neuroimaging Initiative (ADNI)-1 and ADNI-2 observational studies, and the Investigation Into Delay to Diagnosis of Alzheimer's Disease With Exelon (InDDEx) clinical trial – have been standardized to the Clinical Data Interchange Standards Consortium (CDISC) therapeutic-area standards for AD. Briefing documents and face-to-face meetings have been held with the US FDA to finalize the proposed Context of Use Statement for the biomarker, as well as the intended statistical analysis plan. The analysis dataset, consisting of pre-dementia patient-level data from ADNI-1 (n≈305), late pre-dementia from ADNI-2 (n≈122) and InDDEx (n≈394), has been standardized and curated. Imaging data have been re-processed, and ICV-HV was determined by two image analysis algorithms, namely LEAP™ and FreeSurfer™. As per guidance from FDA, temporal changes in Clinical Dementia Rating Scale Sum-of-Boxes (CDR-SB) will be described by a non-linear mixed-effects model. Along with ICV-HV, sex, baseline age and disease severity, and apolipoprotein E genotype will be included as covariates. Clinical trial simulations using the Monte Carlo technique will be performed to compare the statistical power by sample size in trials with and trials without ICV-HV enrichment. The full qualification document will be submitted to the FDA by 3Q 2017. This ongoing biomarker qualification effort with the FDA highlights the importance of understanding disease progression quantitatively to support the qualification of ICV-HV for prognostic purposes. If ICV-HV demonstrates utility in clinical trial enrichment, qualification of this biomarker can streamline drug development programs in AD by insuring the right patients are enrolled into our trials.

Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: A View of the Regulatory Science Qualification Landscape from the Coalition Against Major Diseases CSF Biomarker Team.

Alzheimer’s disease (AD) drug development is burdened with the current requirement to conduct large, lengthy, and costly trials to overcome uncertainty in patient progression and effect size on treatment outcome measures. There is an urgent need for the discovery, development, and implementation of novel, objectively measured biomarkers for AD that would aid selection of the appropriate subpopulation of patients in clinical trials, and presumably, improve the likelihood of successfully evaluating innovative treatment options. Amyloid deposition and tau in the brain, which are most commonly assessed either in cerebrospinal fluid (CSF) or by molecular imaging, are consistently and widely accepted. Nonetheless, a clear gap still exists in the accurate identification of subjects that truly have the hallmarks of AD. The Coalition Against Major Diseases (CAMD), one of 12 consortia of the Critical Path Institute (C-Path), aims to streamline drug development for AD and related dementias by advancing regulatory approved drug development tools for clinical trials through precompetitive data sharing and adoption of consensus clinical data standards. This report focuses on the regulatory process for biomarker qualification, briefly comments on how it contrasts with approval or clearance of companion diagnostics, details the qualifications currently available to the field of AD, and highlights the current challenges facing the landscape of CSF biomarkers qualified as hallmarks of AD. Finally, it recommends actions to accelerate regulatory qualification of CSF biomarkers that would, in turn, improve the efficiency of AD therapeutic development.

Prognostic factors, predictive markers and cancer biology: the triad for successful oral cancer chemoprevention.

Oral squamous cell carcinomas represent a significant cancer burden worldwide. Unfortunately, chemoprevention strategies investigated to date have failed to produce an agent considered standard of care to prevent oral cancers. Nonetheless, recent advances in clinical trial design may streamline drug development in this setting. In this manuscript, we review some of these improvements, including risk prediction tools based on molecular markers that help select patients most suitable for chemoprevention. We also discuss the opportunities that novel preclinical models and modern molecular profiling techniques will bring to the prevention field in the near future, and propose a clinical trials framework that incorporates molecular prognostic factors, predictive markers and cancer biology as a roadmap to improve chemoprevention strategies for oral cancers.

TranSMART Foundation Datathon 1.0: The cross neurodegenerative diseases challenge

The tranSMART Foundation's inaugural Datathon took place June 30–July 2 at the Thomson Reuters offices in Boston, MA. The overall aim of the Datathon was to determine the feasibility of using the tranSMART platform to explore multiple large datasets on a customized cloud server to support a Datathon that could generate new research findings. The goal of this Datathon was to identify similarities and differences across different neurodegenerative diseases, specifically Alzheimer's disease and Parkinson's disease, and to discover new insights into these diseases. Specific objectives were to identify: • Common biomarker changes across Parkinson and Alzheimer disease • Common pathway changes across Parkinson and Alzheimer disease • The normal distribution of imaging and fluid biomarkers across controls • Novel hypotheses, research findings or conclusions about these neurodegenerative diseases. 2. Design The tranSMART Foundation, the Michael J. Fox Foundation, the University of Luxembourg and the University of Michigan worked together with the Laboratory of Neuro Imaging (LONI) to install tranSMART v1.2.4 on cloud servers at LONI, and to install the 14 datasets to be used for the Datathon. The ADNI, PPMI, LRRK2 and BioFIND datasets were curated and loaded by Thomson Reuters, working with the Michael J. Fox Foundation. Due to restrictions on access to and redistribution of the ADNI, PPMI, LRRK2 and BioFIND datasets, data use agreements were executed with the Alzheimer's Data Neuroimaging Initiative, the Parkinson's Progression Markers Initiative, the LRRK2 dataset, led by the Michael J. Fox foundation, and the BIOFIND dataset. Ten datasets that were curated and loaded by the University of Luxembourg originated in GEO, and did not require any data use agreements. This Datathon marked the first time that these datasets have been made available in a single analytic platform. Together the datasets represent over $500 million investment in data generation. ADNI: The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal, multicenter study to develop genetic, biochemical, clinical, and imaging biomarkers for the early detection and progression tracking of Alzheimer's disease. 3142 patients are currently enrolled. PPMI: The Parkinson's Progression Markers Initiative is a longitudinal, multimodal observational study of a large patient population. The dataset contains biological sampling, advanced imaging, clinical and behavioral assessments; i.e. the Movement Disorder Society—Unified Parkinson's Disease Rating Scales (MD-UPDRS), Montreal Cognitive Assessment (MoCA) and the University of Pennsylvania Smell Identification (UPSIT). 1334 patients are currently enrolled. LRRK2: Michael J. Fox Foundation has established a LRRK2 Cohort Consortium to undertake an innovative approach to design and streamline drug development around the LRRK2 gene, a promising target. 2824 patients are currently enrolled. BIOFIND: is a clinical observational study designed to discover and validate novel biomarkers for Parkinson's disease. 229 patients are currently enrolled. 10 Parkinson's Disease (PD) studies from GEO: The NCBI Gene Expression Omnibus (GEO—http://www.ncbi.nlm.nig.gov/). In attempt to exact valuable knowledge, data scientists from the Luxembourg Centre for Systems Biomedicine (http://wwwen.uni.lu/lcsb), University of Luxembourg (http://wwwen.uni.lu) manually curated 10 PD studies from GEO, which are selected based on having good amount of clinical data apart from gene expression data. These studies were curated in the context of ongoing Innovative Medicine Initiate (IMI) project and eTRIKS (http://www.etriks.org). Data from these studies were passed through following workflow: data acquisition, parsing, manual inspections, data standardization, semantic alignment and mapping, the generated structured files are ready to be used as input for the tranSMART ETL (Extraction, Transformation and Loading) operations. The structured files were loaded into tranSMART using the Pentaho Kettle ETL scripts. The tranSMART Foundation, working with the University of Michigan and LONI, installed the platform on LONI cloud servers, and coordinated the installation of the curated datasets onto these servers with Thomson Reuters, the Michael J. Fox Foundation and the University of Luxembourg. The latest tranSMART platform, v1.2.4, was employed for these efforts. Access to the databases permitted participants to evaluate whether modifications were needed to make the data more usable. Twenty-five scientists from leading institutions in the US and Europe were selected from a pool of over seventy applicants five teams.1 In addition to the tranSMART platform, various third-party analytic tools were employed, including MetaCore™, R interface, Spotfire, E-Workbook, MatLab, and REFS™.

‘21st Century Cures’: House committee releases discussion draftto streamline drug development

On January 27, the House Committee on Energy amp; Commercereleased a 393-page discussion draft of bipartisan legislation thatwould set forth goals for streamlining the process of drug developmentand advancing innovations in medicine. Called "21st Century Cures,"it is no small undertaking.

AlzheimerÂ’s and ParkinsonÂ’s Diseases Face Common Challenges in Therapeutic Development: Role of the Precompetitive Consortium, Coalition Against Major Diseases

Alzheimer’s disease (AD) and Parkinson’s disease (PD) pose significant challenges for successful development of new therapies, with anextremely high drug trial failure rate and yet no approved disease modifying drugs available. Given the magnitude of the challenges, it has become clear that larger collaborations and multi-partner joint efforts, pooling resources and expertise,are required for theadvancement of methods and tools that are critically needed to support drug development studies. Critical Path Institute’s Coalition against Major Diseases was formed in 2008, at a time prior to the era of public private partnerships, with the mission of streamlining and de-risking drug development for AD and PD. Since its origin, the consortium has achieved several milestones including development of consensus data standards for AD and PD, a unified clinical trial database comprised of placebo data from AD therapeutic trials and regulatory endorsement of drug development tools. In addition, the consortium is progressing strongly on other initiatives, with ongoing regulatory interactions. The coalition held its annual conference at the U.S. Food and Drug Administration, where diverse stakeholders including industry, academic experts, government agency representatives, patient advocacy organizations and regulators gathered together to share their accomplishments and focus on the needs of the future. The current landscape was emphasized with focus on the need to expand the precompetitive space and enhance data sharing globally.

At the bench: the key role of PK–PD modelling in enabling the early discovery of biologic therapies

Pharmacokinetic-pharmacodynamic (PK-PD) modelling is already used extensively in pre-clinical and clinical drug development to characterize drug candidates quantitatively, aid go/no-go decisions and to inform future trial design and optimal dosing regimens. Less well known, although arguably as powerful, is its application at the earliest stages of drug development, at target selection and lead selection, where these same techniques can be used to predict and so bring forward drug candidates with the necessary characteristics or, for unachievable requirements, allow the abandonment of the programme for the minimum spend of time and cost. We consider three examples that illustrate the power of the application of modelling at this early stage. We start with the simple case of determining the optimal characteristics for a monoclonal antibody against a soluble ligand with its application to the investment decision for the development of best-in-class compounds. This is extended to the more complex situation of the target protein having an endogenous, inhibitory binding protein. We then illustrate how using physiologically-based pharmacokinetic modelling enables the appropriate engineering and testing of biological therapeutics for optimal PK-PD characteristics. These examples illustrate how a minimal investment in modelling achieves orders of magnitude better returns in choosing the correct targets, mechanism of action and candidate characteristics to progress to clinical trials, streamlining drug development and delivering better medicines to patients.

PI3K/AKT/mTOR Signaling Is a Significant Druggable Pathway In Infant Acute Lymphoblastic Leukemia (ALL)

IntroductionInfant acute lymphoblastic leukemia (ALL) is an orphan disease with unmet need for safe effective therapies. This is an urgent problem because conventional chemotherapies are ineffective and have life-threatening toxicities in infants. Although the MLL rearrangements occurring in 75% of cases are associated with poor outcome, survival is inferior whether MLL is rearranged or not. We recently reported that infant ALL proved sensitive to obatoclax mesylate (GeminX Pharmaceuticals; now an indirect, wholly owned subsidiary of Teva Pharmaceutical Industries Ltd.) in vitro regardless of poor prognostic features including MLL gene rearrangement. Moreover, we showed that the leukemia cell killing by obatoclax involved apoptosis, necroptosis and autophagy (Urtishak et al., Blood 2013). Therefore, the recent pharmaceutical abandonment of obatoclax led us to search for similarly acting drugs, the Results of which identified the well-known antipsychotic thioridazine as a candidate for potential repurposing. MethodsCorrelative analyses were performed between basal gene expression profiles at leukemia diagnosis and single agent obatoclax EC50 values from MTT assays in 47 cases of infant ALL from the Children's Oncology Group P9407 trial (25 MLL-AF4; 8 MLL-ENL; 7 other MLL-rearranged; 7 MLL-germline) in order to find a priori determinants of obatoclax sensitivity; significant genes were further studied by Ingenuity Pathway Analysis (IPA). A search for similarly acting compounds was conducted by Connectivity Map analysis of gene expression profiles of MLL-AF4 ALL cell lines after obatoclax treatment. MTT assays without and with cell death pathway inhibition, Western blot and flow cytometric cell death assays, and phosphoflow cytometric signaling analyses were utilized to investigate activity and target modulation by potential candidates. ResultsIPA identified significant correlations between basal gene expression of the mTOR and downstream intersecting eIF4/p70S6K signaling programs and obatoclax EC50 in all 47 primary cases of infant ALL, as well as in the subset of the 25 cases with MLL-AF4 rearrangements. Consistent with the relevance of this pathway in leukemia cell killing that was suggested by the basal gene expression profiles in the primary cases, the Connectivity Map analysis of obatoclax-treated cell lines for compound matching returned a number of highly ranked PI3K/AKT/mTOR signal transduction inhibitors as potential obatoclax substitutes. Three of the compounds (LY294002, wortmannin, thioridazine) were not only cytotoxic in MLL-AF4 ALL cell lines, but also they abrogated PI3K/AKT/mTOR signaling as indicated by robust inhibition of phosphorylated S6. Of these compounds, the phenothiazine derivative thioridazine, which has been used clinically for decades as a neuroleptic, was of high interest because of potential advantages of drug repurposing for more rapid drug advancement. Moreover, detailed flow cytometric and Western blot analyses, and MTT assays of thioridazine in the presence of cell death pathway inhibitors validated activation of all three cell death mechanisms in the MLL-AF4 ALL cell lines similarly to obatoclax. ConclusionsThioridazine is a well-known antipsychotic drug that also has recently recognized properties as a PI3K/AKT/mTOR signaling inhibitor and as an inhibitor of other pathways relevant to cancer. In MLL-AF4 ALL cell lines characterized by the most common chromosomal translocation in infant ALL, single-agent thioridazine is highly cytotoxic, robustly inhibits PI3K/AKT/mTOR signaling and, moreover, like obatoclax, demonstrates activity as a multi-cell-death pathway agonist. Further preclinical studies now are warranted to determine the extent to which thioridazine inhibits PI3K/AKT/mTOR signaling and causes leukemia cell killing in primary infant ALL cells in vitro and in vivo. The repurposing strategy that this drug may allow could have promise to streamline drug development in infant ALL where the need for new therapies is so urgent. [Display omitted] Disclosures:No relevant conflicts of interest to declare.

Modeling NSCLC Progression: Recent Advances and Opportunities Available

Non-small cell lung cancer (NSCLC) is one of the leading causes of death around the world with an estimated 5-year relative survival rate of 16% at diagnosis. Development of drugs treating NSCLC is not easy, and the success rate for an anticancer treatment to pass through the whole clinical development process is as low as 5%. Modeling and simulation lend themselves as tools which can potentially streamline drug development. A critical component of the models developed is a description of how the disease progresses over time and how a treatment would affect its trajectory. Our aim was to review the literature to present the models and growth functions which have been used for describing NSCLC dynamics, and how anticancer treatments can affect such dynamics, both in animals and in humans. Only a limited set of models were identified for such a purpose. Most of the models which have been used were descriptive of tumor growth, yet there were attempts to account for the underlying processes, especially in animals where it is more feasible to collect data needed for developing such models. Moreover, we discuss how modeling and simulation can aid in decision making across the different stages of drug development. Based on some encouraging results from trials of other cancer types where modeling tumor dynamics has played an important role, we propose further exploration of NSCLC using model-based techniques and further use of these techniques in designing and evaluating NSCLC trials.

Screening inhibitors against h1n1 neuraminidase using molecular docking

Prediction of protein in large databases is one of the major research objectives in structural and functional proteomics. Therefore, its amino acid sequence is compared with the sequences of structural database using computational techniques. It needs to be design drugs for diseases which are being caused by proteins whose structure is unknown; In order to streamline computer aided drug discovery and development in the spirit of scientific method. The outbreak of H1N1 influenza pandemic strains that are resistant to currently prescribed antivirals has earmarked the need to develop/screen novel compounds that target viral gene products such as Neuraminidase. Preliminary investigation revealed active site residue dissimilarity with H5N1 Neuraminidase. Screening and comparison of various antiviral drugs by using Bioinformatics techniques. Original anti-flu drugs such as Oseltamivir, Zanamivir etc were allowed to bind within the active region of H5N1 as well as H1N1 neuraminidase to study the affinities. Screenings of various other drugs were performed using Drug Bank database to assess the ability of binding of such drugs and to check the possibility of them as Flu inhibitors. Affinity of binding was performed by GOLD, PATCH Dock and ME dock softwares.

Quantitative Evaluation and Prediction of Drug Effects and Toxicological Risk Using Mechanistic Multiscale Models.

Integrating in vitro and in silico approaches has great potential for reducing experimental effort and delivering know-how and intellectual property in drug development. Here, we focus on a possible framework for multiscale modeling in pharmaceutical drug development. Looking at the modeling frameworks at different scales, it is obvious that choosing the proper level of complexity and abstraction is not a trivial task. At cellular level, we consider that the application of validated kinetic models of cellular toxicity mechanisms of drugs is particularly important for deriving valid predictions. These kinetic models can be applied for integrating inter-individual differences, e.g. obtained from data measured in surgical liver samples, into predictions of drug effects. Challenges identified include (i) the development of sufficiently detailed, structured organ models, (ii) definition of multiscale models that can be efficiently handled by available super-computing facilities, and (iii) availability of validated cell-type and organ-specific kinetic metabolic models. Multiscale models can streamline drug development by facilitating the design of experiments and trials, by providing and testing hypotheses, and by reducing time and costs due to less experiments and improved decision-making. In this review, we discuss the required pieces, possibilities, and challenges in multiscale modeling for the prediction of drug effects.

Developability Index: A Rapid In Silico Tool for the Screening of Antibody Aggregation Propensity

Determining the aggregation propensity of protein-based biotherapeutics is an important step in the drug development process. Typically, a great deal of data collected over a large period of time is needed to estimate the aggregation propensity of biotherapeutics. Thus, candidates cannot be screened early on for aggregation propensity, but early screening is desirable to help streamline drug development. Here, we present a simple molecular computational method to predict the aggregation propensity via hydrophobic interactions, thought to be the most common mechanism of aggregation, and electrostatic interactions. This method uses a new quantity termed Developability Index. It is a function of an antibody's net charge, calculated on the full-length antibody structure, and the spatial aggregation propensity, calculated on the complementarity-determining region structure. Its accuracy is due to the molecular level details and the incorporation of the tertiary structure of the antibody. It is particularly applicable to antibodies or other proteins for which structures are available or could be determined accurately using homology modeling. Applications include the selection of molecules in the discovery or early development process, selection of mutants for stability, and estimation of resources needed for development of a given biomolecule.

Abstract 1764: Horizontal and vertical signal pathway inhibition in human tumor primary culture micro-spheroids

Abstract Introduction: Signal transduction pathways are targets for small molecule tyrosine and serine-threonine kinase inhibitors. Redundancy and cross talk between pathways can complicate the application of genomic signatures but proteomic and functional platforms may more closely approximate tumor phenotypes. We used EVA/PCD (ex vivo analysis of programmed cell death), a functional platform measuring both apoptotic & non-apoptotic events to examine the PI3K and EGFr pathways in human 1° culture micro-spheroids. Methods: 337 tumor specimens provided from the OR were mechanically and enzymatically disaggregated and exposed to EGFr (Gefitinib), AKT (B-15), PI3K (LY294002) & mTOR (Rapamycin) inhibitors with LC50 values interpolated from 5-point dose response curves. Synergy was assessed by median effect and correlation coefficients by Pearson Moment. Results: Parallel Pearson Moment analyses in 51 specimens by 2-tailed T, revealed LY vs. B15 (NS); LY vs. Rapa (P<0.02); B15 vs. Rapa (P<0.0025); Rapa vs. Gefitinib (P <0.001). Synergy analyses for Rapa & Gefitinib revealed synergy in 29%, additivity in 41%, sub-additivity in 13% and antagonism in 17%. Exploratory synergy analyses that combined Gefitinib & LY and Gefitinib & B-15, favored the Gefitinib& B-15 combination with 100% synergy in this small series. Conclusions: EVA/PCD analyses provide insights into cellular response to targeted therapies, alone and in combination. Correlative analyses identify points of commonality and/or disparity in downstream signaling that can be exploited in drug development and therapy. Synergy analyses reveal potentially important drug combinations. The EVA/PCD human tumor micro-spheroid platform provides a functional tool capable of streamlining drug development and cancer therapy. Supported by The Vanguard Cancer Foundation and the Nagourney Institute. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1764.

Phase 0 Clinical Trials: An Answer to Drug Development Stagnation?

action, pharmacology, bioavailability, pharmacodynamics, and metabolic microdose assessments. These studies of novel agents expose a small number of patients (perhaps 10 or fewer) to a limited duration (eg, 7 days or less) and dose (in the range of one 100th of the dose required to yield a pharmacologic effect of the test substance with a maximum dose of 100 g). 3 They are conducted before the traditional phase I dose-escalation safety and tolerance studies. By not having the traditional phase I objectives of toxicity and dose finding, phase 0 studies can be conducted early in the development process and are actually considered more of a discovery, rather than development, tool. In early 2006, the FDA published “A Guidance for Industry, Investigators, and Reviewers for Exploratory IND Studies” as part of the agency’s critical path initiative to streamline drug development and improve the understanding of drugs early in the clinical process. 3 There must be several considerations before initiating a phase 0

FDG-PET/CT for the Evaluation of Response to Therapy of Cutaneous T-cell Lymphoma to Vorinostat (Suberoylanilide Hydroxamic Acid, SAHA) in a Phase II Trial

Harnessing the power of molecular imaging in particular positron emission tomography (PET) to assess response to therapy in early clinical trials has the potential to yield crucial data on efficacy and streamline drug development. Vorinostat (also known as SAHA, suberoylanilide hydroxamic acid) is a histone deacetylase (HDAC) inhibitor which alters gene transcription to inhibit proliferation and promote apoptosis. In a phase II trial of vorinostat for cutaneous T cell lymphoma (CTCL), 2-deoxy-2-[F-18]fluoro-D-glucose (FDG)-PET/computed tomography (CT) was performed on patients with both cutaneous and nodal disease. FDG-PET/CT fuses the power of metabolic imaging from FDG-PET with the anatomic detail of CT. Scans were conducted on subjects pre-therapy and during therapy. Changes in the values of FDG uptake and measurements of nodal dimensions and thickness of cutaneous lesions were tabulated. FDG-PET/CT provided an objective measure of the response (or lack thereof) of both cutaneous and nodal disease to therapy with vorinostat. The results of this study are encouraging for the potential utility of FDG-PET/CT in future trials with HDAC inhibitors for other diseases and for CTCL with other therapies. Further study will be required to determine the prognostic value of the initial PET/CT scan and response on follow-up scans.

Effect of bevacizumab (Bev) on the growth rate constants of renal carcinoma (RCC) tumors

11044 Background: An analysis of the phase II bevacizumab versus placebo trial using a novel algorithm suggests the lack of a overall survival (OS) advantage for bevacizumab may have been a result of early discontinuation of therapy. To hasten cancer drug development, new paradigms, especially ones applicable to pts with metastatic disease, are needed to assess therapeutic efficacy. In a randomized phase II study in pts with RCC, 10 mcg/kg Bev every 2 weeks prolonged time to progression but a statistically significant improvement in OS could not be demonstrated. Methods: We describe a novel method to assess therapeutic efficacy using tumor measurements gathered while a patient receives therapy in a clinical trial. We developed and validated a two-phase equation to estimate concomitant rates of tumor regression (regression rate constant, d) and tumor growth (growth rate constant, g). Results: For pts on placebo, the mean g value was 10-2.231 day-1 compared to a value of 10-2.561 day-1 for pts on 10 mcg/kg Bev (p < 0.001) and in all pts g correlated with OS. By comparison, the differences in d were not statistically significant and although the regression portion of the curve was needed to accurately describe the data, it did not predict OS in these pts with RCC. A log difference of 0.330 in mean g between placebo and 10 mcg/kg Bev could have translated into at least 386 ± 81 days of added OS, not the observed 47 days. That a OS advantage was not demonstrated with Bev appears to have been a result of early discontinuation of Bev. Conclusions: Single agent Bev significantly affects the growth rate constants of RCC and, in pts with metastatic disease, will likely impact OS if continued beyond standard criteria for progressive disease. The mathematical model described herein has applications to many tumor types and should aid in evaluating relative efficacies of different therapies. Modeling tumor progression using data gathered while patients are enrolled on a clinical trial as has been done in the present study may streamline drug development and accelerate drug approval. Consideration should be given to study designs that include an experimental arm in which pts continue therapy despite disease progression beyond arbitrary endpoints. No significant financial relationships to disclose.