Early Phase Drug 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.

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.

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.

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.

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.

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.

Modernizing Clinical Trial Eligibility: Recommendations of the American Society of Clinical Oncology-Friends of Cancer Research Minimum Age Working Group.

Purpose Children have historically been excluded from first-in-human studies of promising new cancer drugs and later phase adult clinical trials. Delays in evaluation may result in off-label use without dosing information as the only access to new drugs. A multistakeholder workshop was convened in May 2016 by ASCO and Friends of Cancer Research to identify opportunities for when it would be scientifically appropriate to expand trial eligibility to include children younger than age 18 years in first-in-human and other adult cancer clinical trials. Methods This group convened experts from academia, government, and industry to review barriers to enrolling children and adolescents in oncology clinical trials. We evaluated the historical context, published literature, regulatory considerations, and myriad risks and benefits associated with lowering the age of enrollment on oncology clinical trials. Results We conclude that many of the historical concerns about including children early in oncology clinical trials do not apply in the current scientific and clinical environment of pediatric oncology and drug development; we provide specific recommendations for how the inclusion of children in early-phase investigational cancer drug trials might be accomplished. Automatic inclusion of pediatric patients is appropriate in early-phase trials that assess dose, safety, and pharmacokinetics in a variety of tumor types and later phase trials that assess efficacy in a specific disease that spans adult and pediatric populations. Conclusion Including children in appropriately designed adult clinical oncology trials is feasible and can be done in a way that enhances their access to these agents without compromising safety or development strategies.

STEIN: A simple toxicity and efficacy interval design for seamless phase I/II clinical trials.

Seamless phase I/II dose-finding trials are attracting increasing attention nowadays in early-phase drug development for oncology. Most existing phase I/II dose-finding methods use sophisticated yet untestable models to quantify dose-toxicity and dose-efficacy relationships, which always renders them difficult to implement in practice. To simplify the practical implementation, we extend the Bayesian optimal interval design from maximum tolerated dose finding to optimal biological dose finding in phase I/II trials. In particular, optimized intervals for toxicity and efficacy are respectively derived by minimizing probabilities of incorrect classifications. If the pair of observed toxicity and efficacy probabilities at the current dose is located inside the promising region, we retain the current dose; if the observed probabilities are outside of the promising region, we propose an allocation rule by maximizing the posterior probability that the response rate of the next dose falls inside a prespecified efficacy probability interval while still controlling the level of toxicity. The proposed interval design is model-free, thus is suitable for various dose-response relationships. We conduct extensive simulation studies to demonstrate the small- and large-sample performance of the proposed method under various scenarios. Compared to existing phase I/II dose-finding designs, not only is our interval design easy to implement in practice, but it also possesses desirable and robust operating characteristics.

An in silico strategy for identification of novel drug targets against Plasmodium falciparum.

The apicomplexan parasite Plasmodium falciparum is responsible for global malaria burden. With the reported resistance to artemisinin chemotherapy, there is an urgent need to maintain early phase drug discovery and identify novel drug targets for successful eradication of the pathogen from the host. In our previous work on comparative genomics study for identification of putative essential genes and therapeutic candidates in P. falciparum, we predicted 11 proteins as anti-malarial drug targets from PlasmoDB database. In this paper, we made an attempt for identification of novel drug targets in P. falciparum genome using a sequence of computational methods from Malaria Parasite Metabolic Pathway database. The study reported the identification of 71 proteins as potential drug targets for anti-malarial interventions. Furthermore, homology modeling and molecular dynamic simulation study of one of the potential drug targets, aminodeoxychorismate lyase, was carried to predict the 3D structure of the protein. Structure and ligand-based drug designing reported MMV019742 from Pathogen Box and TCAMS-141515 from GSK-TCAMS library as potential hits. The reliability of the binding mode of the inhibitors is confirmed by GROMACS for a simulation time of 20ns in water environment. This will be helpful for experimental validation of the small-molecule inhibitor.

EXPLORING NOVEL COGNITIVE AND ELECTROPHYSIOLOGICAL MARKERS OF TARGET ENGAGEMENT IN PHASE 1 AND 2 STUDIES OF PUTATIVE CHOLINERGIC COGNITIVE ENHANCERS

Loss of cholinergic signaling is principally related to cognitive decline in Alzheimer's Disease (AD), and stimulation of these receptors improves cognitive performance. While acetylcholinesterase inhibitors are modestly helpful in the early stages of AD, neurodegeneration limits their effectiveness, and warrants the development of alternative cholinergic treatments. Given the high costs of drug development, it is important to obtain evidence of target engagement as early as possible. Phase 1 and 2 studies provide an opportunity not only to establish maximum tolerated doses and safety, but also to document cognitive effects in human subjects. Development of novel behavioral and brain-based measures targeting cognitive processes of interest and sensitive to the drug effects will accelerate efficacy evaluation. We report evidence from early phase drug trials using event-related potentials (ERP) and cholinergically-responsive psychomotor cognitive tasks developed in our laboratory as markers of CNS engagement. We explored whether treatment may potentiate cholinergic receptors in the CNS in humans by evaluating changes in electroencephalography (EEG) functions (e.g. altered ERPs). Oddball and memory ERP tasks were used to evaluate the cognitive impact of four-week chronic nicotine treatment on memory (indexed by increased ERP amplitudes for repeated vs. novel stimuli and better performance on a Selective Reminding Task) in aging adults with Down syndrome (DS), a single-gene model of AD. ERP passive memory testing demonstrated positive drug effects on cognitive performance compared to standard verbal memory tasks that were difficult for DS subjects to perform. In addition, computerized cognitive assessment of basic sensory and psychomotor functions utilizing critical flicker fusion and decomposition of choice reaction time detected subtle cognitive effects of cholinergic agents in volunteers. We are currently using the same ERP and sensory/psychomotor measures to examine the effects of a novel cholinergic positive allosteric modulator (PAM) to establish functional biomarkers of central target engagement in healthy young adults.

Fluorometric evaluation of CYP3A4 expression using improved transgenic HepaRG cells carrying a dual-colour reporter for CYP3A4 and CYP3A7

Primary human hepatocytes are necessary to evaluate cytotoxicity, drug metabolism, and drug–drug interactions for candidate compounds in early-phase drug discovery and development. However, these analyses are often hampered by limited resources and functional or genetic variation among lots. HepaRG human hepatocellular carcinoma cells can differentiate into mature hepatocyte-like cells (HepLCs) that possess similar metabolic activity to human hepatocytes. We previously established transgenic HepaRG cells carrying a dual reporter that express red fluorescent protein (RFP) under the transcriptional regulation of CYP3A7 in the hepatoblast-like cell state and enhanced green fluorescent protein (EGFP) under the transcriptional regulation of CYP3A4 following HepLC differentiation. In this study, we successfully isolated a subclone of transgenic CYP3A4G/7R HepaRG cells with an improved HepLC differentiation potency. Midazolam metabolism by CYP3A4 in these HepLCs was comparable to that in wild-type HepLCs. The EGFP fluorescence intensity was greatly induced by rifampicin (RIF) treatment. There was a strong correlation between fluorometric and metabolic analyses. The fold change in EGFP-positive cells was comparable to those in the CYP3A4 mRNA level and luminescence of proluciferin metabolites. RIF treatment and cell proliferation increased the RFP-positive cell number. Thus, CYP3A4G/7R HepLCs provide a real-time, multiwell-based system to co-evaluate CYP3A4 induction and hepatic regeneration.

Design early phase drug combination trials: software

Design early phase drug combination trials: software

Design early phase drug combination trials: methods

Design early phase drug combination trials: methods