Rapid progress in neuroimaging technologies fuels central nervous system translational medicine.

Central nervous system (CNS) drug discovery suffers from high attrition rates; translational neuroscience approaches aiming to reduce these high rates include the use of brain imaging technologies. However, there is a need to better understand what methods are being used and for what diseases and purposes. Our analysis of the literature found that magnetic resonance imaging (MRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) were the neuroimaging techniques used most often in clinical trials for the most prevalent CNS diseases: Alzheimer's disease (AD), Parkinson's disease (PD), depression, and schizophrenia. Moreover, the number of initiated clinical trials using MRI, PET, and SPECT increased over the period 1981-2021. Such insights indicate that the significant increase in the use of neuroimaging studies could decrease the attrition of novel drug candidates in late clinical development.

A Useful and Sustainable Role for N-of-1 Trials in the Healthcare Ecosystem.

Clinicians and patients often try a treatment for an initial period to inform longer-term therapeutic decisions. A more rigorous approach involves N-of-1 trials. In these single-patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double-blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N-of-1 trial design as type 1, there also are new and evolving uses of N-of-1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N-of-1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual-patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N-of-1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value-based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N-of-1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N-of-1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N-of-1 trials.

A Survey of Survival Outcomes for Targeted Cancer Drugs Approved by the US Food and Drug Administration.

BACKGROUND: The last two decades have witnessed the vigorous development of targeted cancer drugs and the potent therapeutic effects of these drugs have been validated by various true and surrogate end points. Overall survival (OS) and progression-free survival (PFS) outcomes were two important end points used in targeted cancer drugs clinical trials but investigation on which was rare as a consequence of inherent heterogeneity and complexity. Here, we present the review and analysis of OS and PFS outcomes of all targeted cancer drugs approved by the U.S. Food and Drug Administration (FDA) through December 31, 2019, in the setting of clinical studies. METHODS: The targeted cancer drug directory was accessed via NCI website. The survival outcomes of those drugs in the setting of clinical trials were collected from publicly available Package Inserts and ClinicalTrials.gov. Median overall (OS) and progression-free survival (PFS) outcomes were summarized for targeted cancer drugs that were evaluated as monotherapies in clinical trials, contributions of targeted drugs to combination therapies in terms of survival benefit were analyzed, survival outcomes of FDA-approved first-line targeted therapies in different cancers were investigated, and the correlation between the absolute OS gain (ΔOS) and PFS gain (ΔPFS) as well as the hazard ratios for PFS (HRPFS) and OS (HROS) between comparative arms of available randomized clinical trials was evaluated. RESULTS: A total of 223 indications for 126 targeted cancer drugs have been approved by the FDA through December 31, 2019, among which 28 indications of 23 drugs have been approved for first-line therapies. Eighty indications for leukemia, lymphoma, and rare cancer types without survival data were excluded in the investigation of survival outcomes. For the remaining 143 indications, 99 were approved as monotherapies and 72 were approved as combination therapies. Among monotherapy subset, 18 of 72 (25%) indications with available OS outcomes have maximum median OS less than 12 months, 55 of 72 (76%) drug indications have maximum median OS less than 24 months, and 67 of 72 (93%) have maximum median OS less than 36 months. Regarding PFS, 38 of 88 (43%) drug indications have maximum median PFS less than 6 months, 69 of 88 (78%) drug indications have maximum median PFS less than 12 months, and 84 of 88 (95%) drug indications have maximum median PFS less than 24 months. The addition of targeted drugs to combination regimens under FDA's approval provided notable survival benefit, but the median value of OS gain rate of the available combination regimens was lower than that of PFS. The univariate Spearman Rank correlation coefficient suggested a significant positive correlation between ΔOS and ΔPFS (R = 0.62) but a weak correlation between HROS and HRPFS (R = 0.11) in 46 randomized clinical trials that investigated contributions of targeted cancer drugs to combination therapies with available data. A moderate correlation between ΔOS and ΔPFS (R = 0.43) and a rather weak correlation between HROS and HRPFS (R = 0.07) were also found in other randomized clinical trials that included in our study with available data. CONCLUSIONS: The survival benefit provided by targeted cancer drugs varied a lot among cancer types. Though targeted cancer drugs showed improvements in both OS and PFS in approved combination regimens, the median value of OS gain rate was lower than that of PFS. As only weak correlation was found between HRPFS and HROS, the evidence supporting the use of PFS as a surrogate to OS in the setting of targeted cancer drugs might also be limited.

Are Regulation and Innovation Priorities Serving Public Health Needs?

A host of challenges confront healthcare authorities worldwide. Topping the list is the demand for innovative new medicines to treat a range of both infectious and non-communicable diseases, while containing spiraling healthcare costs. The challenge is particularly great in therapeutic areas where, despite significant medical need and economic impact, the technical challenges and commercial risk of development serve as disincentives to drug sponsors. These areas include cardiovascular diseases as well as diseases and disorders of the central nervous system. Currently, the development and approval of new active substances, with its disproportionate focus on oncology, is not in alignment with healthcare needs in most geographic regions. In this article, we discuss the origins of this misalignment and suggest various approaches to address healthcare needs going forward.

Efficacy and Effectiveness Too Trials: Clinical Trial Designs to Generate Evidence on Efficacy and on Effectiveness in Wide Practice.

Efficacy trials, designed to gain regulatory marketing approval, evaluate drugs in optimally selected patients under advantageous conditions for relatively short time periods. Effectiveness trials, designed to evaluate use in usual practice, assess treatments among more typical patients in real-world conditions with longer follow-up periods. In "efficacy-to-effectiveness (E2E) trials," if the initial efficacy trial component is positive, the trial seamlessly transitions to an effectiveness trial component to efficiently yield both types of evidence. Yet more time could be saved by simultaneously addressing efficacy and effectiveness in an "efficacy and effectiveness too (EE2) trial." Additionally, hybrids of the E2E and EE2 approaches with differing degrees of overlap of the two components could allow flexibility for specific drug development needs. In planning EE2 trials, each stakeholder's current and future needs, incentives, and perspective must be considered. Although challenging, the ultimate benefits to stakeholders, the health system, and the public should justify this effort.

EFFICACY-TO-EFFECTIVENESS CLINICAL TRIALS.

Efficacy trials, which assess treatments in optimally selected patients under advantageous conditions for relatively short time periods, are necessary to gain regulatory approval for marketing. In contrast, effectiveness trials, which test treatments across a spectrum of patients in real-world conditions with follow-up periods that match typical treatment regimens, provide critical information on drug effects in those patients who may ultimately receive the treatment. We previously proposed a study design that integrates efficacy and effectiveness trials into a 2-component "efficacy-to-effectiveness (E2E) trial," in which if the initial efficacy trial component is positive, then the trial immediately and seamlessly transitions to the effectiveness trial component. However, we believe that total study duration could be even further shortened by simultaneously addressing efficacy and effectiveness too (EE2). An EE2 trial rigorously demonstrates efficacy, but uses broad inclusion characteristics of effectiveness trials. An example of a study using EE2 design, the IMMEDIATE (Immediate Myocardial Metabolic enhancement During Initial Assessment and Treatment in Emergency Care) trial, is provided.

Landscape of Innovation for Cardiovascular Pharmaceuticals: From Basic Science to New Molecular Entities.

PURPOSE: This study examines the complete timelines of translational science for new cardiovascular therapeutics from the initiation of basic research leading to identification of new drug targets through clinical development and US Food and Drug Administration (FDA) approval of new molecular entities (NMEs) based on this research. METHODS: This work extends previous studies by examining the association between the growth of research on drug targets and approval of NMEs associated with these targets. Drawing on research on innovation in other technology sectors, where technological maturity is an important determinant in the success or failure of new product development, an analytical model was used to characterize the growth of research related to the known targets for all 168 approved cardiovascular therapeutics. FINDINGS: Categorizing and mapping the technological maturity of cardiovascular therapeutics reveal that (1) there has been a distinct transition from phenotypic to targeted methods for drug discovery, (2) the durations of clinical and regulatory processes were significantly influenced by changes in FDA practice, and (3) the longest phase of the translational process was the time required for technology to advance from initiation of research to a statistically defined established point of technology maturation (mean, 30.8 years). IMPLICATIONS: This work reveals a normative association between metrics of research maturation and approval of new cardiovascular therapeutics and suggests strategies for advancing translational science by accelerating basic and applied research and improving the synchrony between the maturation of this research and drug development initiatives.

Quantifying the magnitude and cost of collecting extraneous protocol data.

Although most research professionals believe that protocol designs contain a growing number of unnecessary and redundant procedures generating unused data, incurring high cost, and jeopardizing study success, there are no published studies systematically examining this issue. Between November 2011 and May 2012, Tufts Center for the Study of Drug Development conducted a study among a working group of 15 pharmaceutical companies in which a total of 25,103 individual protocol procedures were evaluated and classified using clinical study reports and analysis plans. The results show that the typical later-stage protocol had an average of 7 objectives and 13 end points of which 53.8% are supplementary. One (24.7%) of every 4 procedures performed per phase-III protocol and 17.7% of all phase-II procedures per protocol were classified as "Noncore" in that they supported supplemental secondary, tertiary, and exploratory end points. For phase-III protocols, 23.6% of all procedures supported regulatory compliance requirements and 15.9% supported those for phase-II protocols. The study also found that on average, $1.7 million (18.5% of the total) is spent in direct costs to administer Noncore procedures per phase-III protocol and $0.3 million (13.1% of the total) in direct costs are spent on Noncore procedures for each phase-II protocol. Based on the results of this study, the total direct cost to perform Noncore procedures for all active annual phase-II and phase-III protocols is conservatively estimated at $3.7 billion annually, not including the indirect costs associated with collecting and managing Noncore procedure data and the ethical costs of exposing study volunteers to unnecessary risks associated with conducting extraneous procedures.

Taking the pulse of strategic outsourcing relationships.

PURPOSE: Articles in peer-reviewed journals and the trade press presuppose that strategic outsourcing relationships have been formed to replace preexisting collaborative approaches with contract research organizations. They do not consider that large, fragmented pharmaceutical and biotechnology companies may be supporting competing and conflicting relationship models simultaneously. A recent Tufts Center for the Study of Drug Development study quantifies actual strategic outsourcing practices among drug development companies and sheds new light on why these relationships may be failing. METHODS: Tufts Center for the Study of Drug Development conducted an in-depth assessment of 43 Phase II and III clinical studies completed since 2012 to examine the outsourcing relationships used by 9 major pharmaceutical and biotechnology companies to support key functional areas. Descriptive statistics were assessed and t tests were performed to characterize outsourcing practices by function and to determine differences in study performance between transactional and strategic outsourcing relationships. FINDINGS: The results indicate that sponsor companies are using a variety of outsourcing relationship models to support their studies, mixing and matching the use of internal staff, and using traditional transactional and strategic outsourcing relationships simultaneously. Specifically, despite the fact that each sponsor company had entered into several strategic outsourcing relationships, in no instance did a single contract research organization manage all functional areas supporting an individual Phase II or III study. In addition, sponsor companies vary the types of outsourcing relationship models that they use on a study-by-study basis. IMPLICATIONS: The inability of pharmaceutical and biotechnology companies to consistently embrace and coordinate sourcing strategies is creating internal friction and inefficiency. As a result, the expected impact of strategic outsourcing relationships on drug development performance, quality, and cost remains elusive.