Early Phases Of Drug Development Research Articles

Seamless Designs: Current Practice and Considerations for Early-Phase Drug Development in Oncology.

Traditionally, drug development has evaluated dose, safety, activity, and comparative benefit in a sequence of phases using trial designs and endpoints specifically devised for each phase. Innovations in drug development seek to consolidate the phases and rapidly expand accrual with “seamless” trial designs. Although consolidation and rapid accrual may yield efficiencies, widespread use of seamless first-in-human (FiH) trials without careful consideration of objectives, statistical analysis plans, or trial oversight raises concerns. A working group formed by the National Cancer Institute convened to consider and discuss opportunities and challenges for such trials as well as encourage responsible use of these designs. We reviewed all abstracts presented at American Society of Clinical Oncology annual meetings from 2010 to 2017 for FiH trials enrolling at least 100 patients. We identified 1786 early-phase trials enrolling 57 559 adult patients. Fifty-one of the trials (2.9%) investigated 50 investigational new drugs, were seamless, and accounted for 14.6% of the total patients. The seamless trials included a median of 3 (range = 1–13) expansion cohorts. The overall risk of clinically significant treatment-related adverse events (grade 3–4) was 49.1% (range = 0.0–100%), and seven studies reported at least one toxic death. Rapid expansion of FiH trials may lead to earlier drug approval and corresponding widespread patient access to active therapeutics. Nevertheless, seamless designs must adhere to established ethical, scientific, and statistical standards. Protocols should include prospectively planned analyses of efficacy in disease- or biomarker-defined cohorts of sufficient rigor to support accelerated approval.

The Association for Human Pharmacology in the Pharmaceutical Industry London Meeting 2018: Brexit and Other Challenges in Early Phase Drug Development.

The Association for Human Pharmacology in the Pharmaceutical Industry (AHPPI) annual meeting focused on the changing face of early phase drug development and opened with a keynote speech concerning the revolution in pharmaceutical medicine over the last 30 years and the impact this has had on the way patients are treated. Examples were presented of how translational pharmaceutics is being used to tackle the high drug candidate failure rate and is improving productivity when moving drug candidates from the laboratory through to clinical proof of concept. The European Medicines Agency revised 2007 Risk Mitigation guideline on first in human (FIH) clinical trials was discussed. The focus of the revised guideline, which came into force in February 2018, is on risk mitigation and promotion of safety and will assist drug sponsors with the design and performance of early clinical studies. The use of integrated adaptive protocol designs in early clinical development was discussed in relation to the challenges involved when running early phase clinical trials in patients. The Health Regulatory Authority presented its strategies to ensure that following Brexit, the United Kingdom remains an attractive place to conduct Phase I clinical trials. The Medicines and Healthcare products Regulatory Agency confirmed that in the event of a “no deal” Brexit, it is well placed to implement and influence many provisions of the new EU CTR. The meeting provided an opportunity to discuss the changing regulatory environment and the opportunities and challenges facing the United Kingdom following Brexit with invited speakers from a range of disciplines including drug development, clinical trials and research organizations, government science policy and regulatory agencies.

Learning from the past to design better trials in second-line treatment for mesothelioma patients.

Malignant pleural mesothelioma (MPM) is an aggressive cancer characterised by modest sensitivity to systemic chemotherapy. The standard treatment remains platinum-based chemotherapy with pemetrexed. Recently, the addition of an antiangiogenic drug, bevacizumab, to first-line chemotherapy has been shown to improve overall survival. All the patients, unfortunately, will progress, and currently, there is no standard treatment approved in second-line. Recently, the results of the NGR015 phase III randomised with NGR-hTNF plus chemotherapy versus placebo in addition to physician’s choice second-line chemotherapy for MPM have been published. Despite encouraging data achieved in previous phase I and phase II studies, the NGR-hTNF drug failed to meet the primary endpoint of the study, although a signal of activity was observed in the group of patients who had a shorter treatment failure interval from the first-line treatment.Hereby, we start from this recent trial to highlight once more the importance of thoroughly investigating possible predictive factors during the early drug development phase to allow more efficient phase III trial design, thus avoiding the possibility of potentially effective molecules like NGR-hTNF, continuing to be wasted.

Molecularly Targeted Therapy for Neuroblastoma.

Neuroblastoma is the most common extra-cranial solid tumor encountered in childhood and accounts for 15% of pediatric cancer-related deaths. Although there has been significant improvement in the outcomes for patients with high-risk disease, the therapy needed to achieve a cure is quite toxic and for those that do experience a disease recurrence, the prognosis is very dismal. Given this, there is a tremendous need for novel therapies for children with high-risk neuroblastoma and the molecular discoveries over recent years provide hope for developing new, less toxic, and potentially more efficacious treatments. Here I discuss many of the molecular aberrations identified thus far in neuroblastoma, as well as the agents in development to target these changes. The progress made in both the preclinical arena and in early phase drug development provide much promise for the future of precision medicine in neuroblastoma.

Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials.

Late-onset toxicity is common for novel molecularly targeted agents and immunotherapy. It causes major logistic difficulty for existing adaptive phase I trial designs, which require the observance of toxicity early enough to apply dose-escalation rules for new patients. The same logistic difficulty arises when the accrual is rapid. We propose the time-to-event Bayesian optimal interval (TITE-BOIN) design to accelerate phase I trials by allowing for real-time dose assignment decisions for new patients while some enrolled patients' toxicity data are still pending. Similar to the rolling six design, the TITE-BOIN dose-escalation/deescalation rule can be tabulated before the trial begins, making it transparent and simple to implement, but is more flexible in choosing the target dose-limiting toxicity (DLT) rate and has higher accuracy to identify the MTD. Compared with the more complicated model-based time-to-event continuous reassessment method (TITE-CRM), the TITE-BOIN has comparable accuracy to identify the MTD but is simpler to implement with substantially better overdose control. As the TITE-CRM is more aggressive in dose escalation, it is less likely to underdose patients. When there are no pending data, the TITE-BOIN seamlessly reduces to the BOIN design. Numerical studies show that the TITE-BOIN design supports continuous accrual without sacrificing patient safety or the accuracy of identifying the MTD, and therefore has great potential to accelerate early-phase drug development. Clin Cancer Res; 24(20); 4921-30. ©2018 AACR.

Paracetamol-induced liver injury modelled in Xenopus laevis embryos

IntroductionFailure to predict drug-induced liver injury (DILI) remains a major contributing factor to lead compound drop-out during drug development. Xenopus embryos are amenable for early stage medium throughput small molecule screens and so have the potential to be used in pre-clinical screens. To begin to assess the usefulness and limitations of Xenopus embryos for safety assessment in the early phases of drug development, paracetamol was used as a model hepatotoxin. Paracetamol overdose is associated with acute liver injury. In mammals, the main mechanism of paracetamol-induced acute liver injury is an increased amount of the reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI) combined with a reduction of free glutathione (GSH). Humans that have taken an overdose of paracetamol are often treated with N-acetyl cysteine (NAC). MethodXenopus laevis embryos were treated with up to 5 mM paracetamol from stage 38 to stage 45 during development, when the liver is functional. The presence of paracetamol-induced liver injury was assessed by: (1) microRNA-122 (miR-122) expression (a hepatic marker), (2) free GSH concentration (a marker of oxidative stress) and (3) NAC antioxidant intervention. ResultsThe amount of free GSH decreased significantly in embryos exposed to increasing paracetamol concentration. In embryos exposed to 5 mM paracetamol, 22.57 ± 4.25 nmol/mg GSH was detected compared to 47.11 ± 7.31 nmol/mg untreated embryos (mean ± SEM). In tail tissue, miRNA-122 expression increased 6.3-fold with 3 mM paracetamol concentration treatment compared to untreated embryos. NAC treatment altered the free GSH decline for embryos treated with up to 5 mM. Embryos exposed to 1 mM paracetamol and then exposed to 0.5 mM NAC 24 h prior to harvest, had a significantly higher amount of GSH compared to embryos that were only exposed to 1 mM paracetamol (mean ± SEM; 97.1 ± 9.6 nmol/mg and 54.5 ± 6.6 nmol/mg respectively). ConclusionXenopus laevis embryos exhibit similar characteristics of paracetamol-induced liver injury observed in mammalian models. These data indicate that the Xenopus embryo could be a useful in vivo model to assess DILI and aid lead compound prioritisation during the early phase of drug development, in combination with pre-clinical in vitro studies. Consequently, the Xenopus embryo could contribute to the reduction principle as defined by the National Centre for the Replacement, Refinement and Reduction of Animals in Research.

Abstract 2288: Assessing patient trial readiness for precision cancer medicine clinical trials through computational trial matching and rule-based logic applied to genomic and clinical data

Abstract More than 1,100 phase I treatment trials are registered with clinicaltrials.cancer.gov. Patient identification and recruitment to these trials is particularly challenging due to the vast molecular data now available for patients and the increasingly complex nature of the molecular eligibility criteria. Additionally, Phase I trial staff often manage a portfolio of dozens of trials, making patient identification, recruitment, screening, and enrollment an arduous task. To address the need for better and more efficient patient identification, we have developed MatchMiner, a novel open source computational platform for matching patient-specific genomic profiles to precision cancer medicine clinical trials, and a pre-screening tool that includes options for filtering and sorting patients based on clinical data elements. MatchMiner excels at identifying patients who are eligible for clinical trials based on genomic, cancer type, age, and gender criteria, but the great majority of patients are not currently ready for a trial. The pre-screening tool allows for the integration of additional clinical data, including genomic testing date, appointments, treatment plan history, and radiology scan impression text, in order to provide an assessment of ‘trial readiness'. To integrate these tools into the clinical workflow, we have implemented a weekly MatchMiner Tumor Board Review process, where together with the DFCI Early-Phase Drug Development Center (EDDC) physicians and staff, a thorough assessment of potential patient-trial matches is performed. Currently we have scaled this initiative to include 18 genomically-driven trials. Each week, ~9000 patient-trial matches are computed across all open trials, which are then computationally filtered to a list of ~300 patient-trial matches utilizing rules-based logic applied to our clinical data sources. The MatchMiner team then performs a manual review of pre-filtered matches based on additional requirements, such as evidence of progression in the radiology scan text impressions. The final list of ~10-20 patients is reviewed with the EDDC, and patients deemed to be ‘trial ready' are flagged. E-mail notifications are then sent out to the patient's oncologist, alerting them to a potential genomically-driven clinical trial opportunity. The combination of computational patient-trial match identification and rules-based computational pre-filtering based on additional clinical data has allowed us to screen thousands of patients per week, which would not be possible otherwise. To evaluate the success of this initiative, we are tracking patient consults and trial enrollments, and capturing feedback on workflow integration and utilization. Additionally, efforts to further automate trial readiness measurements to minimize the need for manual review are ongoing. Citation Format: Catherine Del Vecchio Fitz, Khanh Do, James Lindsay, Suzanne Hector-Barry, Zachary Zwiesler, Priti Kumari, Tali Mazor, Tamba Monrose, Adem Albayrak, John Methot, Michael Hassett, Geoffrey Shapiro, Ethan Cerami. Assessing patient trial readiness for precision cancer medicine clinical trials through computational trial matching and rule-based logic applied to genomic and clinical data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2288.

Optimization of Primary Drying in Lyophilization During Early-Phase Drug Development Using a Definitive Screening Design With Formulation and Process Factors

Development of optimal drug product (DP) lyophilization cycles is typically accomplished via multiple engineering runs to determine appropriate process parameters. These runs require significant time and product investments, which are especially costly during early phase development when the DP formulation and lyophilization process are often defined simultaneously. Even small changes in the formulation may require a new set of engineering runs to define lyophilization process parameters. To overcome these development difficulties, an 8 factor definitive screening design, including both formulation and process parameters, was executed on a fully human monoclonal antibody DP. The definitive screening design enables evaluation of several interdependent factors to define critical parameters that affect primary drying time and product temperature. From these parameters, a lyophilization development model is defined where near optimal process parameters can be derived for many different DP formulations. This concept is demonstrated on a monoclonal antibody DP where statistically predicted cycle responses agree well with those measured experimentally. This design of experiments approach for early phase lyophilization cycle development offers a workflow that significantly decreases the development time of clinically and potentially commercially viable lyophilization cycles for a platform formulation that still has variable range of compositions.

Emerging immunotherapy and decade of early phase drug development: Systematic review of multiple myeloma treatment.

e20016Background: With the emergence of immunotherapy, genomics, and precision medicine, the future of multiple myeloma (MM) treatment is rapidly evolving. We reviewed the efficacy of (non-FDA appr...

Effect profile of paracetamol, Δ9-THC and promethazine using an evoked pain test battery in healthy subjects.

A battery of evoked pain tasks (PainCart) was developed to investigate the pharmacodynamic properties of novel analgesics in early-phase clinical research. As part of its clinical validation, compounds with different pharmacological mechanisms of actions are investigated. The aim was to investigate the analgesic effects of classic and nonclassic analgesics compared to a sedating negative control in a randomized placebo-controlled crossover study in 24 healthy volunteers using the PainCart. The PainCart consisted of pain tasks eliciting electrical, pressure, heat, cold and inflammatory pain. Subjective scales for cognitive functioning and psychotomimetic effects were included. Subjects were administered each of the following oral treatments: paracetamol (1000mg), Δ9-THC (10mg), promethazine (50mg) or matching placebo. Pharmacodynamic measurements were performed at baseline and repeated up to 10h postdose. Paracetamol did not show a significant reduction in pain sensation or subjective cognitive functioning compared to placebo. Promethazine induced a statistically significant reduction in PTT for cold pressor and pressure stimulation. Furthermore, reduced subjective alertness was observed. Δ9-THC showed a statistically significant decrease in PTT for electrical and pressure stimulation. Δ9-THC also demonstrated subjective effects, including changes in alertness and calmness, as well as feeling high and psychotomimetic effects. This study found a decreased pain tolerance due to Δ9-THC and promethazine, or lack thereof, using an evoked pain task battery. Pain thresholds following paracetamol administration remained unchanged, which may be due to insufficient statistical power. We showed that pain thresholds determined using this pain test battery are not driven by sedation. The multimodal battery of evoked pain tasks utilized in this study may play an important role in early-phase clinical drug development. This battery of pain tasks is not sensitive to the effects of sedation alone, and thus suitable to investigate the analgesic potential of novel analgesic compounds.

Standards and Methodological Rigor in Pulmonary Arterial Hypertension Preclinical and Translational Research.

Despite advances in our understanding of the pathophysiology and the management of pulmonary arterial hypertension (PAH), significant therapeutic gaps remain for this devastating disease. Yet, few innovative therapies beyond the traditional pathways of endothelial dysfunction have reached clinical trial phases in PAH. Although there are inherent limitations of the currently available models of PAH, the leaky pipeline of innovative therapies relates, in part, to flawed preclinical research methodology, including lack of rigour in trial design, incomplete invasive hemodynamic assessment, and lack of careful translational studies that replicate randomized controlled trials in humans with attention to adverse effects and benefits. Rigorous methodology should include the use of prespecified eligibility criteria, sample sizes that permit valid statistical analysis, randomization, blinded assessment of standardized outcomes, and transparent reporting of results. Better design and implementation of preclinical studies can minimize inherent flaws in the models of PAH, reduce the risk of bias, and enhance external validity and our ability to distinguish truly promising therapies form many false-positive or overstated leads. Ideally, preclinical studies should use advanced imaging, study several preclinical pulmonary hypertension models, or correlate rodent and human findings and consider the fate of the right ventricle, which is the major determinant of prognosis in human PAH. Although these principles are widely endorsed, empirical evidence suggests that such rigor is often lacking in pulmonary hypertension preclinical research. The present article discusses the pitfalls in the design of preclinical pulmonary hypertension trials and discusses opportunities to create preclinical trials with improved predictive value in guiding early-phase drug development in patients with PAH, which will need support not only from researchers, peer reviewers, and editors but also from academic institutions, funding agencies, and animal ethics authorities.

Prediction of Phase Behavior of Spray-Dried Amorphous Solid Dispersions: Assessment of Thermodynamic Models, Standard Screening Methods and a Novel Atomization Screening Device with Regard to Prediction Accuracy.

The evaluation of drug–polymer miscibility in the early phase of drug development is essential to ensure successful amorphous solid dispersion (ASD) manufacturing. This work investigates the comparison of thermodynamic models, conventional experimental screening methods (solvent casting, quench cooling), and a novel atomization screening device based on their ability to predict drug–polymer miscibility, solid state properties (Tg value and width), and adequate polymer selection during the development of spray-dried amorphous solid dispersions (SDASDs). Binary ASDs of four drugs and seven polymers were produced at 20:80, 40:60, 60:40, and 80:20 (w/w). Samples were systematically analyzed using modulated differential scanning calorimetry (mDSC) and X-ray powder diffraction (XRPD). Principal component analysis (PCA) was used to qualitatively assess the predictability of screening methods with regards to SDASD development. Poor correlation was found between theoretical models and experimentally-obtained results. Additionally, the limited ability of usual screening methods to predict the miscibility of SDASDs did not guarantee the appropriate selection of lead excipient for the manufacturing of robust SDASDs. Contrary to standard approaches, our novel screening device allowed the selection of optimal polymer and drug loading and established insight into the final properties and performance of SDASDs at an early stage, therefore enabling the optimization of the scaled-up late-stage development.

Moving beyond the comprehensive in vitro proarrhythmia assay: Use of human-induced pluripotent stem cell-derived cardiomyocytes to assess contractile effects associated with drug-induced structural cardiotoxicity.

Drug-induced cardiotoxicity is a potentially severe side effect that can adversely affect myocardial contractility through structural or electrophysiological changes in cardiomyocytes. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are a promising human cardiac in vitro model system to assess both proarrhythmic and non-proarrhythmic cardiotoxicity of new drug candidates. The scalable differentiation of hiPSCs into cardiomyocytes provides a renewable cell source that overcomes species differences present in current animal models of drug toxicity testing. The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative represents a paradigm shift for proarrhythmic risk assessment, and hiPSC-CMs are an integral component of that paradigm. The recent advancements in hiPSC-CMs will not only impact safety decisions for possible drug-induced proarrhythmia, but should also facilitate risk assessment for non-proarrhythmic cardiotoxicity, where current non-clinical approaches are limited in detecting this risk before initiation of clinical trials. Importantly, emerging evidence strongly suggests that the use of hiPSC-CMs with cardiac physiological relevant measurements in vitro improves the detection of structural cardiotoxicity. Here we review high-throughput drug screening using the hiPSC-CM model as an experimentally feasible approach to assess potential contractile and structural cardiotoxicity in early phase drug development. We also suggest that the assessment of structural cardiotoxicity can be added to electrophysiological tests in the same platform to complement the Comprehensive in vitro Proarrhythmia Assay for regulatory use. Ideally, application of these novel tools in early drug development will allow for more reliable risk assessment and lead to more informed regulatory decisions in making safe and effective drugs available to the public.

Developing Drugs for Heart Failure With Reduced Ejection Fraction: What Have We Learned From Clinical Trials?

There remains a large unmet need for new therapies in the treatment of heart failure with reduced ejection fraction (HFrEF). In the early drug development phase, the therapeutic potential of a drug is not yet fully understood and trial endpoints other than mortality are needed to guide drug development decisions. While a true surrogate marker for mortality in heart failure (HF) remains elusive, the successes and failures of previous trials can reveal markers that support clinical Go/NoGo decisions.

Subgroup identification in dose-finding trials via model-based recursive partitioning.

An important task in early-phase drug development is to identify patients, which respond better or worse to an experimental treatment. While a variety of different subgroup identification methods have been developed for the situation of randomized clinical trials that study an experimental treatment and control, much less work has been done in the situation when patients are randomized to different dose groups. In this article, we propose new strategies to perform subgroup analyses in dose-finding trials and discuss the challenges, which arise in this new setting. We consider model-based recursive partitioning, which has recently been applied to subgroup identification in 2-arm trials, as a promising method to tackle these challenges and assess its viability using a real trial example and simulations. Our results show that model-based recursive partitioning can be used to identify subgroups of patients with different dose-response curves and improves estimation of treatment effects and minimum effective doses compared to models ignoring possible subgroups, when heterogeneity among patients is present.

Mechanistic ligand-receptor interaction model: operational model of agonism.

This tutorial explains the basic principles of mechanistic ligand-receptor interaction model, which is an operational model of agonism. A growing number of agonist drugs, especially immune oncology drugs, is currently being developed. In this tutorial, time-dependent ordinary differential equation for simple Emax operational model of agonism was derived step by step. The differential equation could be applied in a pharmacodynamic modeling software, such as NONMEM, for use in non-steady state experiments, in which experimental data are generated while the interaction between ligand and receptor changes over time. Making the most of the non-steady state experimental data would simplify the experimental processes, and furthermore allow us to identify more detailed kinetics of a potential drug. The operational model of agonism could be useful to predict the optimal dose for agonistic drugs from in vitro and in vivo animal pharmacology experiments at the very early phase of drug development.

Alzheimer's disease drug development pipeline: 2018

IntroductionTreatments for Alzheimer's disease (AD) are needed due to the growing number of individuals with preclinical, prodromal, and dementia forms of AD. Drug development for AD therapies can be examined by inspecting the drug development pipeline as represented on clinicaltrials.gov. MethodsClinicaltrials.gov was assessed as of January 30, 2018 to determine AD therapies represented in phase I, phase II, and phase III. ResultsThere are 112 agents in the current AD treatment pipeline. There are 26 agents in 35 trials in phase III, 63 agents in 75 trials in phase II, and 23 agents in 25 trials in phase I. A review of the mechanisms of actions of the agents in the pipeline shows that 63% are disease-modifying therapies, 22% are symptomatic cognitive enhancers, and 12% are symptomatic agents addressing neuropsychiatric and behavioral changes. Trials in phase III are larger and longer than phase II or phase I trials, particularly those involving disease-modifying agents. Comparison with the 2017 pipeline shows that there are four new agents in phase III, 14 in phase II, and eight in phase I. Inspection of the use of biomarkers as revealed on clinicaltrials.gov shows that amyloid biomarkers are used as entry criterion in 14 phase III disease-modifying agent trials and 17 disease-modifying agent trials in phase II. Twenty-one trials of disease-modifying agents in phase II did not require biomarker confirmation for AD at trial entry. DiscussionThe AD drug development pipeline is slightly larger in 2018 than in 2017. Trials increasingly include preclinical and prodromal populations. There is an increase in nonamyloid mechanisms of action for drugs in earlier phases of drug development. Biomarkers are increasingly used in AD drug development but are not used uniformly for AD diagnosis confirmation.

Efficient design of integrated and adaptively interlinked early phase drug development programs

Efficient design of integrated and adaptively interlinked early phase drug development programs

Process and scaling parameters for wet media milling in early phase drug development: A knowledge based approach

Wet media milling is a well-established unit operation for the manufacturing of suspension formulations during early phase pharmaceutical development. However, knowledge about the kinetics of particle breakage is limited, although the impact of hydro-mechanical process parameters on the mean particle size of finished suspensions has been thoroughly investigated. We performed in this work milling trials with two different compounds on two milling devices with different mechanical design and volume scale. We analyzed our data in terms of a kinetic milling model where we included the milling speed as an explicit process parameter in addition to the process duration. We show, that the milling kinetics can be fairly well predicted for a wide range of these operating parameters. The proposed milling model may therefore be useful for rational process planning and scale-up considerations in the industrial setting.

Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays.

Human liver contains various oxidative and conjugative enzymes that can convert nontoxic parent compounds to toxic metabolites or, conversely, toxic parent compounds to nontoxic metabolites. Unlike primary hepatocytes, which contain myriad drug-metabolizing enzymes (DMEs), but are difficult to culture and maintain physiological levels of DMEs, immortalized hepatic cell lines used in predictive toxicity assays are easy to culture, but lack the ability to metabolize compounds. To address this limitation and predict metabolism-induced hepatotoxicity in high-throughput, we developed an advanced miniaturized three-dimensional (3D) cell culture array (DataChip 2.0) and an advanced metabolizing enzyme microarray (MetaChip 2.0). The DataChip is a functionalized micropillar chip that supports the Hep3B human hepatoma cell line in a 3D microarray format. The MetaChip is a microwell chip containing immobilized DMEs found in the human liver. As a proof of concept for generating compound metabolites in situ on the chip and rapidly assessing their toxicity, 22 model compounds were dispensed into the MetaChip and sandwiched with the DataChip. The IC50 values obtained from the chip platform were correlated with rat LD50 values, human C max values, and drug-induced liver injury categories to predict adverse drug reactions in vivo. As a result, the platform had 100% sensitivity, 86% specificity, and 93% overall predictivity at optimum cutoffs of IC50 and C max values. Therefore, the DataChip/MetaChip platform could be used as a high-throughput, early stage, microscale alternative to conventional in vitro multi-well plate platforms and provide a rapid and inexpensive assessment of metabolism-induced toxicity at early phases of drug development.