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While the drug development literature provides numerous estimates of the financial costs to bring a new drug to market, the investment of patient-participants in the research process has not been described. Trial participants and their caregivers, like companies, invest time and undertake risk when they participate in prelicense trials. We determined the average number of patient-participants needed to develop a novel neurological drug. We created a cohort of 108 unapproved drugs first tested for efficacy between 2006 and 2011 and used ClinicalTrials.gov to capture enrollment in all subsequent prelicense trials of these drugs over a 9-year period. Our primary outcome was the average number of patients enrolled in prelicense neurological drug trials per drug that ultimately attained FDA approval, including patients who participated in both successful and unsuccessful development efforts. Five drugs (4.6%) were FDA approved, and 66,751 patient-participants were enrolled across successful and unsuccessful drug development efforts, resulting in an average of 13,350 patients for each drug attaining approval (95% CI 7155 to 54,954). Our estimates reveal the substantial amount patients and their caregivers contribute to private drug development.

The authors review the timelines, and probabilities, of recent vaccines progressing from phase 2 clinical trials to licensure within 10 years., Visual Abstract. Probability of Success and Timelines of Vaccines for Viral Infectious Diseases The authors review the timelines, and probabilities, of recent vaccines progressing from phase 2 clinical trials to licensure within 10 years. Visual Abstract. Probability of Success and Timelines of Vaccines for Viral Infectious Diseases The authors review the timelines, and probabilities, of recent vaccines progressing from phase 2 clinical trials to licensure within 10 years., Background: Anticipated success rates and timelines for COVID-19 vaccine development vary. Recent experience with developing and testing viral vaccine candidates can inform expectations regarding the development of safe and effective vaccines. Objective: To estimate timelines and probabilities of success for recent vaccine candidates. Design: ClinicalTrials.gov was searched to identify trials testing viral vaccines that had not advanced to phase 2 before 2005, and the progress of each vaccine from phase 1 through to U.S. Food and Drug Administration (FDA) licensure was tracked. Trial characteristics were double-coded. (Registration: Open Science Framework [https://osf.io/dmuzx/]). Setting: Trials launched between January 2005 and March 2020. Participants: Preventive viral vaccine candidates for 23 emerging or reemerged viral infectious diseases. Measurements: The primary end point was the probability of vaccines advancing from launch of phase 2 to FDA licensure within 10 years. Results: In total, 606 clinical trials forming 220 distinct development trajectories (267 343 enrolled participants) were identified. The probability of vaccines progressing from phase 2 to licensure within 10 years was 10.0% (95% CI, 2.6% to 16.9%), with most approvals representing H1N1 or H5N1 vaccines. The average timeline from phase 2 to approval was 4.4 years (range, 6.4 weeks to 13.9 years). The probabilities of advancing from phase 1 to 2, phase 2 to 3, and phase 3 to licensure within the total available follow-up time were 38.2% (CI, 30.7% to 45.0%), 38.3% (CI, 23.1% to 50.5%), and 61.1% (CI, 3.7% to 84.3%), respectively. Limitations: The study did not account for preclinical development and relied primarily on ClinicalTrials.gov and FDA resources. Success probabilities do not capture the varied reasons why vaccines fail to advance to regulatory approval. Conclusion: Success probabilities and timelines varied widely across different vaccine types and diseases. If a SARS-CoV-2 vaccine is licensed within 18 months of the start of the pandemic, it will mark an unprecedented achievement for noninfluenza viral vaccine development. Primary Funding Source: McGill Interdisciplinary Initiative in Infection and Immunity (MI4) Emergency COVID-19 Research Funding program.

The lionfish (Pterois volitans) is a venomous invasive species found in the Caribbean and Northwestern Atlantic. It poses a growing health problem because of the increase in frequency of painful stings, for which no treatment or antidote exists, and the long-term disability caused by the pain. Understanding the venom's algogenic properties can help identify better treatment for these envenomations. In this study, we provide the first characterization of the pain and inflammation caused by lionfish venom and examine the mechanisms through which it causes pain using a combination of in vivo and in vitro approaches including behavioral, physiological, calcium imaging, and electrophysiological testing. Intraplantar injections of the venom produce a significant increase in pain behavior, as well as a marked increase in mechanical sensitivity for up to 24 hours after injection. The algogenic substance(s) are heat-labile peptides that cause neurogenic inflammation at the site of injection and induction of Fos and microglia activation in the superficial layers of the dorsal horn. Finally, calcium imaging and electrophysiology experiments show that the venom acts predominantly on nonpeptidergic, TRPV1-negative, nociceptors, a subset of neurons implicated in sensing mechanical pain. These data provide the first characterization of the pain and inflammation caused by lionfish venom, as well as the first insight into its possible cellular mechanism of action.

ObjectiveTo determine whether patients randomized to unapproved, disease-modifying interventions in neurodegenerative disease trials have better outcomes than patients randomized to placebo by performing a systematic review and meta-analysis of risk and benefit experienced by patients in randomized placebo-controlled trials testing investigational treatments for Alzheimer disease, Parkinson disease, Huntington disease, or amyotrophic lateral sclerosis (ALS).MethodsWe searched MEDLINE, Embase, and ClinicalTrials.gov for results of randomized trials testing non–Food and Drug Administration–approved, putatively disease-modifying interventions from January 2005 to May 2018. Trial characteristics were double-extracted. Coprimary endpoints were the treatment advantage over placebo on efficacy (standardized mean difference in outcomes) and safety (risk ratios of serious adverse events and withdrawals due to adverse events), calculated with random effects meta-analyses. The study was registered on PROSPERO (CRD42018103798).ResultsWe included 113 trials (n = 39,875 patients). There was no significant efficacy advantage associated with assignment to putatively disease-modifying interventions compared to placebo for Alzheimer disease (standardized mean difference [SMD] −0.03, 95% confidence interval [CI] −0.07 to 0.01), Parkinson disease (SMD −0.09, 95% CI −0.32 to 0.15), ALS (SMD 0.02, 95% CI −0.25 to 0.30), or Huntington disease (0.02, 95% CI −0.27 to 0.31). Patients with Alzheimer disease assigned to active treatment were at higher risk of experiencing serious adverse events (risk ratio [RR] 1.15, 95% CI 1.04–1.27) and withdrawals due to adverse events (RR 1.44, 95% CI 1.21–1.70).ConclusionsAssignment to active treatment was not beneficial for any of the indications examined and may have been slightly disadvantageous for patients with Alzheimer disease. Our findings suggest that patients with neurodegenerative diseases are not, on the whole, harmed by assignment to placebo when participating in trials.

ObjectiveTo explore the accuracy of combined neurology expert forecasts in predicting primary endpoints for trials.MethodsWe identified one major randomized trial each in stroke, multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS) that was closing within 6 months. After recruiting a sample of neurology experts for each disease, we elicited forecasts for the primary endpoint outcomes in the trial placebo and treatment arms. Our main outcome was the accuracy of averaged predictions, measured using ordered Brier scores. Scores were compared against an algorithm that offered noncommittal predictions.ResultsSeventy-one neurology experts participated. Combined forecasts of experts were less accurate than a noncommittal prediction algorithm for the stroke trial (pooled Brier score = 0.340, 95% subjective probability interval [sPI] 0.340 to 0.340 vs 0.185 for the uninformed prediction), and approximately as accurate for the MS study (pooled Brier score = 0.107, 95% confidence interval [CI] 0.081 to 0.133 vs 0.098 for the noncommittal prediction) and the ALS study (pooled Brier score = 0.090, 95% CI 0.081 to 0.185 vs 0.090). The 95% sPIs of individual predictions contained actual trial outcomes among 44% of experts. Only 18% showed prediction skill exceeding the noncommittal prediction. Independent experts and coinvestigators achieved similar levels of accuracy.ConclusionIn this first-of-kind exploratory study, averaged expert judgments rarely outperformed noncommittal forecasts. However, experts at least anticipated the possibility of effects observed in trials. Our findings, if replicated in different trial samples, caution against the reliance on simple approaches for combining expert opinion in making research and policy decisions.

SummaryMechanotransduction, the conversion of mechanical stimuli into electrical signals, is a fundamental process underlying several physiological functions such as touch and pain sensing, hearing and proprioception. This process is carried out by specialized mechanosensitive ion channels whose identities have been discovered for most functions except pain sensing. Here we report the identification of TACAN (Tmem120A), an essential subunit of the mechanosensitive ion channel responsible for sensing mechanical pain. TACAN is expressed in a subset of nociceptors, and its heterologous expression increases mechanically-evoked currents in cell lines. Purification and reconstitution of TACAN in synthetic lipids generates a functional ion channel. Finally, knocking down TACAN decreases the mechanosensitivity of nociceptors and reduces behavioral responses to mechanical but not to thermal pain stimuli, without affecting the sensitivity to touch stimuli. We propose that TACAN is a pore-forming subunit of the mechanosensitive ion channel responsible for sensing mechanical pain.

Mechanotransduction, the conversion of mechanical stimuli into electrical signals, is a fundamental process underlying essential physiological functions such as touch and pain sensing, hearing, and proprioception. Although the mechanisms for some of these functions have been identified, the molecules essential to the sense of pain have remained elusive. Here we report identification of TACAN (Tmem120A), an ion channel involved in sensing mechanical pain. TACAN is expressed in a subset of nociceptors, and its heterologous expression increases mechanically evoked currents in cell lines. Purification and reconstitution of TACAN in synthetic lipids generates a functional ion channel. Finally, a nociceptor-specific inducible knockout of TACAN decreases the mechanosensitivity of nociceptors and reduces behavioral responses to painful mechanical stimuli but not to thermal or touch stimuli. We propose that TACAN is an ion channel that contributes to sensing mechanical pain.

Key Points Question How many patient study participants are needed to obtain a first US Food and Drug Administration approval for a new anticancer drug or biologic therapy? Findings In this cohort study of 120 drugs and biologic therapies, more than 12 000 patients participated in prelicense clinical trials for every new drug or biologic approved by the US Food and Drug Administration. When confined to drugs and biologic interventions with intermediate to substantial clinical impact, nearly 40 000 patients were required per approval. Meaning These results indicate that in addition to involving large private expenses, oncology drug and biologic development entails a large subsidy of altruism, time, and welfare from patients themselves., This cohort study estimates the volume of patients required to achieve a first US Food and Drug Administration (FDA) approval for a new anticancer drug or biologic therapy., Importance Several studies have estimated the financial inputs for successful drug development. Such analyses do not capture the large investment that patient study participants commit to drug development. Objective To estimate the volume of patients required to achieve a first US Food and Drug Administration (FDA) approval for a new anticancer drug or biologic therapy. Design, Setting, and Participants This cohort study included a random sample of prelicense oncology drugs and biologics with a trial site in the United States that were launched into clinical efficacy testing between January 1, 2006, and December 31, 2010. Drugs and biologics were identified using ClinicalTrials.gov registration records. Total patient enrollment was captured over an 8-year span, and each intervention was classified based on whether it received FDA approval and was deemed as having intermediate or substantial value according to the American Society of Clinical Oncology Value Framework (ASCO-VF) score. Secondarily, the association between patient numbers and intervention characteristics was tested. Data were analyzed in February 2020. Main Outcomes and Measure The prespecified primary outcome was the number of patients enrolled in prelicense trials per FDA approval. Results A total of 120 drugs and biologics were included in our study, with 84 (70.0%) targeted agents, 20 (16.7%) immunotherapies, and 71 (59.2%) novel agents. A total of 13 drugs and biologics (10.8%; 95% CI, 5.3%-16.8%) in our sample gained FDA approval within 8 years, of which 1 (7.7%) was deemed of intermediate value and 3 (23.1%) were deemed of substantial value using ASCO-VF scoring. Overall, 158 810 patients were enrolled in 1335 trials testing these drugs and biologics, 47 913 (30.2%) in trials that led to FDA approval and 110 897 (69.8%) in trials that did not. An estimated 12 217 (95% CI, 7970-22 215) patient study participants contributed to prelicense trials per FDA approval. The estimated number of patients needed to produce a single FDA-approved drug or biologic of intermediate or substantial ASCO-VF clinical value was 39 703 (95% CI, 19 391-177 991). Conclusions and Relevance The results of this cohort study make visible the substantial patient investment required for prelicense oncology drug development. Such analyses can be used to devise policies that maximize the clinical impact of research on a per-patient basis.

The process of developing new and complex stem-cell-based therapeutics is incremental and requires decades of sustained collaboration among different stakeholders. In this Perspective, we address key ethical and policy challenges confronting the clinical translation of stem-cell-based interventions (SCBIs), including premature diffusion of SCBIs to clinical practice, assessment of risk in trials, obtaining valid informed consent for research participants, balanced and complete scientific reporting and public communications, regulation, and equitable access to treatment. We propose a way forward for translating these therapies with the above challenges in mind.

Neurofeedback relying on functional magnetic resonance imaging (fMRI-nf) heralds new prospects for self-regulating brain and behavior. Here we provide the first comprehensive review of the fMRI-nf literature and the first systematic database of fMRI-nf findings. We synthesize information from 99 fMRI-nf experiments-the bulk of currently available data. The vast majority of fMRI-nf findings suggest that self-regulation of specific brain signatures seems viable; however, replication of concomitant behavioral outcomes remains sparse. To disentangle placebo influences and establish the specific effects of neurofeedback, we highlight the need for double-blind placebo-controlled studies alongside rigorous and standardized statistical analyses. Before fMRI-nf can join the clinical armamentarium, research must first confirm the sustainability, transferability, and feasibility of fMRI-nf in patients as well as in healthy individuals. Whereas modulating specific brain activity promises to mold cognition, emotion, thought, and action, reducing complex mental health issues to circumscribed brain regions may represent a tenuous goal. We can certainly change brain activity with fMRI-nf. However, it remains unclear whether such changes translate into meaningful behavioral improvements in the clinical domain.

In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination.