From adaptive licensing to adaptive pathways: delivering a flexible life-span approach to bring new drugs to patients

Evolving assessment pathways for precision oncology medicines to improve patient access: a tumor-agnostic lens

BACKGROUND

Genomic and molecular alterations are increasingly important in cancer diagnosis, and scientific advances are opening new treatment avenues. Precision oncology (PO) uses a patient's genomic profile to determine optimal treatment, promising fewer side effects and higher success rates. Within PO, tumor-agnostic (TA) therapies target genomic alterations irrespective of tumor location. However, traditional value frameworks and approval pathways pose challenges which may limit patient access to PO therapies.

OBJECTIVES

This study describes challenges in assessing PO and TA medicines, explores possible solutions, and provides actionable recommendations to facilitate an iterative life-cycle assessment of these medicines.

METHODS

After reviewing the published literature, we obtained insights from key stakeholders and European experts across a range of disciplines, through individual interviews and an industry workshop. The research was guided and refined by an international expert committee through 2 sounding board meetings.

RESULTS

The current challenges faced by PO and TA medicines are multiple and can be demonstrated through real-world examples of the current barriers and opportunities. A life-cycle approach to assessment should be taken, including key actions at the early stages of evidence generation, regulatory and reimbursement stage, as well as payment and adoption solutions that make use of the evolving evidence base. Working toward these solutions to maximize PO medicine value is a shared responsibility and stands to benefit all stakeholders.

CONCLUSIONS

Our call to action is to expand access to comprehensive genomic testing, foster a learning health care system, enable fast and equitable access to cost-effective treatments, and ultimately improve health outcomes.

Design differences and variation in results between randomised trials and non-randomised emulations: meta-analysis of RCT-DUPLICATE data

Objective

To explore how design emulation and population differences relate to variation in results between randomised controlled trials (RCT) and non-randomised real world evidence (RWE) studies, based on the RCT-DUPLICATE initiative (Randomised, Controlled Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology).

Design

Meta-analysis of RCT-DUPLICATE data.

Data sources

Trials included in RCT-DUPLICATE, a demonstration project that emulated 32 randomised controlled trials using three real world data sources: Optum Clinformatics Data Mart, 2004-19; IBM MarketScan, 2003-17; and subsets of Medicare parts A, B, and D, 2009-17.

Eligibility criteria for selecting studies

Trials where the primary analysis resulted in a hazard ratio; 29 RCT-RWE study pairs from RCT-DUPLICATE.

Results

Differences and variation in effect sizes between the results from randomised controlled trials and real world evidence studies were investigated. Most of the heterogeneity in effect estimates between the RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: treatment started in hospital (which does not appear in health insurance claims data), discontinuation of some baseline treatments at randomisation (which would have been an unusual care decision in clinical practice), and delayed onset of drug effects (which would be under-reported in real world clinical practice because of the relatively short persistence of the treatment). Adding the three emulation differences to the meta-regression reduced heterogeneity from 1.9 to almost 1 (absence of heterogeneity).

Conclusions

This analysis suggests that a substantial proportion of the observed variation between results from randomised controlled trials and real world evidence studies can be attributed to differences in design emulation.

The FAIRification of research in real-world evidence: A practical introduction to reproducible analytic workflows using Git and R

Transparency and reproducibility are major prerequisites for conducting meaningful real-world evidence (RWE) studies that are fit for decision-making. Many advances have been made in the documentation and reporting of study protocols and results, but the principles for version control and sharing of analytic code in RWE are not yet as established as in other quantitative disciplines like computational biology and health informatics. In this practical tutorial, we aim to give an introduction to distributed version control systems (VCS) tailored toward the FAIR (Findable, Accessible, Interoperable, and Reproducible) implementation of RWE studies. To ease adoption, we provide detailed step-by-step instructions with practical examples on how the Git VCS and R programming language can be implemented into RWE study workflows to facilitate reproducible analyzes. We further discuss and showcase how these tools can be used to track changes, collaborate, disseminate, and archive RWE studies through dedicated project repositories that maintain a complete audit trail of all relevant study documents.

DESIGN DIFFERENCES EXPLAIN VARIATION IN RESULTS BETWEEN RANDOMIZED TRIALS AND THEIR NON-RANDOMIZED EMULATIONS

Objectives

While randomized controlled trials (RCTs) are considered a standard for evidence on the efficacy of medical treatments, non-randomized real-world evidence (RWE) studies using data from health insurance claims or electronic health records can provide important complementary evidence. The use of RWE to inform decision-making has been questioned because of concerns regarding confounding in non-randomized studies and the use of secondary data. RCT-DUPLICATE was a demonstration project that emulated the design of 32 RCTs with non-randomized RWE studies. We sought to explore how emulation differences relate to variation in results between the RCT-RWE study pairs.

Methods

We include all RCT-RWE study pairs from RCT-DUPLICATE where the measure of effect was a hazard ratio and use exploratory meta-regression methods to explain differences and variation in the effect sizes between the results from the RCT and the RWE study. The considered explanatory variables are related to design and population differences.

Results

Most of the observed variation in effect estimates between RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: (i) in-hospital start of treatment (not observed in claims data), (ii) discontinuation of certain baseline therapies at randomization (not part of clinical practice), (iii) delayed onset of drug effects (missed by short medication persistence in clinical practice).

Conclusions

This analysis suggests that a substantial proportion of the observed variation between results from RCTs and RWE studies can be attributed to design emulation differences. (238 words).

RAPID framework for improved access to precision oncology for lethal disease: Results from a modified multi-round delphi study

Introduction

Predictive oncology, germline technologies, and adaptive seamless trials are promising advances in the treatment of lethal cancers. Yet, access to these therapies is stymied by costly research, regulatory barriers, and structural inequalities worsened by the COVID-19 pandemic.

Methods

To address the need for a comprehensive strategy for rapid and more equitable access to breakthrough therapies for lethal cancers, we conducted a modified multi-round Delphi study with 70 experts in oncology, clinical trials, legal and regulatory processes, patient advocacy, ethics, drug development, and health policy in Canada, Europe, and the US. Semi-structured ethnographic interviews (n = 33) were used to identify issues and solutions that participants subsequently evaluated in a survey (n = 47). Survey and interview data were co-analyzed to refine topics for an in-person roundtable where recommendations for system change were deliberated and drafted by 26 participants.

Results

Participants emphasized major issues in patient access to novel therapeutics including burdens of time, cost, and transportation required to complete eligibility requirements or to participate in trials. Only 12% of respondents reported satisfaction with current research systems, with "patient access to trials" and "delays in study approval" the topmost concerns.

Conclusion

Experts agree that an equity-centered precision oncology communication model should be developed to improve access to adaptive seamless trials, eligibility reforms, and just-in-time trial activation. International advocacy groups are a key mobilizer of patient trust and should be involved at every stage of research and therapy approval. Our results also show that governments can promote better and faster access to life-saving therapeutics by engaging researchers and payors in an ecosystem approach that responds to the unique clinical, structural, temporal, and risk-benefit situations that patients with life-threatening cancers confront.

Understanding variation in the results of real-world evidence studies that seem to address the same question

OBJECTIVES

Multiple database studies on the same question, conducted by different investigators using different approaches or different data sources, can be considered sensitivity analyses for the same causal treatment effect question. We evaluated the contribution of alternative study design parameters and analysis choices to variation in estimates of the risk of major bleeding with dabigatran compared with warfarin.

STUDY DESIGN AND SETTING

We followed a 7-step process: (1) identify published studies asking the same question, (2) independently reproduce selected studies in the same data sources as the original authors, (3) contact original authors, (4) evaluate validity, (5) document critical study parameter specifications, (6) implement a designed matrix of variations in study parameters based on the original studies, and (7) evaluate contributors to variation in results.

RESULTS

Most variation remained unexplained (60-88%). Of the explained variation, two-thirds were related to data and population differences, and one-third were related to the use of alternative study design and analysis parameters. Among these, the most prominent were differences in outcome algorithms and criteria used to define follow-up.

CONCLUSION

When making policy decisions based on database study findings, it is important to evaluate the validity, consistency, and robustness of results to alternative design and analysis decisions.

[Evidence-based health care with pharmaceuticals for rare diseases: the role of digitalisation]

Knowledge generation in the field of drug development for people with rare diseases (RDs) faces particular difficulties. This paper will show what improvements are expected from increasing digitalisation from the perspective of three healthcare institutions: the Federal Institute for Drugs and Medical Devices, the Institute for Quality and Efficiency in Health Care and the Federal Joint Committee.First, the potential of digitalisation to increase the efficiency of clinical development and regulatory decision-making through earlier collaboration of all stakeholders is proposed. Subsequently, it is argued that digitalisation should be used to reduce barriers to the implementation of care-associated randomised controlled trials, including those based on registries. High-quality registry studies should not only be started after approval but during the approval process, so that the evidence necessary for therapy decisions is available promptly after approval. Finally, it is stated that improving the evidence base through qualitative improvement of the data sources and their linkages directly benefits patients. Usable evidence that can be generated over a longer period of time - also beyond approval - and contribute to decisions within healthcare system ensures effective drug provision.The institutions agree that high-quality indication registries should be developed as product-independent, standing infrastructures so that high-quality data can be accessed early in the development of medicines for RD.

Reproducibility of real-world evidence studies using clinical practice data to inform regulatory and coverage decisions

Studies that generate real-world evidence on the effects of medical products through analysis of digital data collected in clinical practice provide key insights for regulators, payers, and other healthcare decision-makers. Ensuring reproducibility of such findings is fundamental to effective evidence-based decision-making. We reproduce results for 150 studies published in peer-reviewed journals using the same healthcare databases as original investigators and evaluate the completeness of reporting for 250. Original and reproduction effect sizes were positively correlated (Pearson’s correlation = 0.85), a strong relationship with some room for improvement. The median and interquartile range for the relative magnitude of effect (e.g., hazard ratio_original/hazard ratio_reproduction) is 1.0 [0.9, 1.1], range [0.3, 2.1]. While the majority of results are closely reproduced, a subset are not. The latter can be explained by incomplete reporting and updated data. Greater methodological transparency aligned with new guidance may further improve reproducibility and validity assessment, thus facilitating evidence-based decision-making. Study registration number: EUPAS19636.

Analyses of real-world evidence from digital clinical practice data provide important insights for healthcare decision makers. Here, authors test reproducibility of 150 peer-reviewed studies, reporting strong reproducibility, which could be further improved through more complete reporting in future original studies

Challenges and Opportunities With Routinely Collected Data on the Utilization of Cancer Medicines. Perspectives From Health Authority Personnel Across 18 European Countries

Background: Rising expenditure for new cancer medicines is accelerating concerns that their costs will become unsustainable for universal healthcare access. Moreover, early market access of new oncology medicines lacking appropriate clinical evaluation generates uncertainty over their cost-effectiveness and increases expenditure for unknown health gain. Patient-level data can complement clinical trials and generate better evidence on the effectiveness, safety and outcomes of these new medicines in routine care. This can support policy decisions including funding. Consequently, there is a need for improving datasets for establishing real-world outcomes of newly launched oncology medicines.

Aim: To outline the types of available datasets for collecting patient-level data for oncology among different European countries. Additionally, to highlight concerns regarding the use and availability of such data from a health authority perspective as well as possibilities for cross-national collaboration to improve data collection and inform decision-making.

Methods: A mixed methods approach was undertaken through a cross-sectional questionnaire followed-up by a focus group discussion. Participants were selected by purposive sampling to represent stakeholders across different European countries and healthcare settings. Descriptive statistics were used to analyze quantifiable questions, whilst content analysis was employed for open-ended questions.

Results: 25 respondents across 18 European countries provided their insights on the types of datasets collecting oncology data, including hospital records, cancer, prescription and medicine registers. The most available is expenditure data whilst data concerning effectiveness, safety and outcomes is less available, and there are concerns with data validity. A major constraint to data collection is the lack of comprehensive registries and limited data on effectiveness, safety and outcomes of new medicines. Data ownership limits data accessibility as well as possibilities for linkage, and data collection is time-consuming, necessitating dedicated staff and better systems to facilitate the process. Cross-national collaboration is challenging but the engagement of multiple stakeholders is a key step to reach common goals through research.

Conclusion: This study acts as a starting point for future research on patient-level databases for oncology across Europe. Future recommendations will require continued engagement in research, building on current initiatives and involving multiple stakeholders to establish guidelines and commitments for transparency and data sharing.

A Framework for Visualizing Study Designs and Data Observability in Electronic Health Record Data

Background

There is growing interest in using evidence generated from clinical practice data to support regulatory, coverage and other healthcare decision-making. A graphical framework for depicting longitudinal study designs to mitigate this barrier was introduced and has found wide acceptance. We sought to enhance the framework to contain information that helps readers assess the appropriateness of the source data in which the study design was applied.

Methods

For the enhanced graphical framework, we added a simple visualization of data type and observability to capture differences between electronic health record (EHR) and other registry data that may have limited data continuity and insurance claims data that have enrollment files.

Results

We illustrate the revised graphical framework with 2 example studies conducted using different data sources, including administrative claims only, EHR only, linked claims and EHR, as well as specialty community based EHRs with and without external linkages.

Conclusion

The enhanced visualization framework is important because evaluation of study validity needs to consider the triad of study question, design, and data together. Any given data source or study design may be appropriate for some questions but not others.

The value of anticancer drugs - a regulatory view

The high prices of new anticancer drugs and the marginal added benefit perceived by some stakeholders have fuelled a debate on the value of anticancer drugs in the European Union, even though an agreed definition of what constitutes a drug's value does not exist. In this Perspective, we discuss the value of drugs from different viewpoints and objectives of decision makers: for regulators, assessment of the benefit-risk balance of a drug is a cornerstone for approval; payers rely on cost-effectiveness analyses carried out by health technology assessment agencies for reimbursement decisions; for patients, treatment choices are based on personal preferences and attitudes to risk; and clinicians can use several scales (such as the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS)) that have been developed as an attempt to measure value objectively. Although a unique definition that fully captures the concept of value is unlikely to emerge, herein we discuss the importance of understanding different perspectives, and how regulators can help to inform different decision makers.

Conditional Drug Approval as a Path to Market for Oncology Drugs in Canada: Challenges and Recommendations for Assessing Eligibility and Regulatory Responsiveness

International drug regulators use conditional drug approval mechanisms to facilitate faster patient access to drugs based on a lower evidentiary standard typically required of drug approvals. Faster and earlier access is justified by limiting eligibility to drugs intended for serious and life-threatening diseases and by requiring post-market evidence collection to confirm clinical benefit. One such mechanism in Canada, the Notice of Compliance with Conditions (NOC/c) policy, was introduced in 1998. Today, most of the drugs approved under the NOC/c policy are for oncology indications. We analyze oncology drugs approvals under the NOC/c policy to inform discussions of two tradeoffs applied to conditional drug approvals, eligibility criteria and post-market evidence. Our analysis informs recommendations for Canada's proposed regulatory reforms approach to conditional approvals pathways. Our analysis demonstrates that under the current policy, eligibility criteria are insufficiently defined, resulting in their inconsistent application by Health Canada. Regulatory responsiveness to post-market evidence from post-market clinical trial and foreign jurisdiction regulatory decisions is slow and insufficient. In the absence of sufficient regulatory responsiveness, physicians and patients must make clinical decisions without the benefit of the best available evidence. Together, our analysis of the two core tradeoffs in Canada's conditional drug approval provides insight to inform the further development of Canada's proposed agile regulatory approach to drugs and devices that will expand the use of terms and conditions.

Innovative Pediatric Development for Secukinumab in Psoriasis: Faster Patient Access, Reduction of Patients on Control

This manuscript describes the innovative pediatric development strategy of secukinumab in psoriasis. Initially, this pediatric development had been planned early during the adult development program. This is common for most development programs as it is required by law in major regions worldwide. At that time, only limited experience with secukinumab's mechanism of action was available, especially in the pediatric population for which no data had been collected yet. Pediatric extrapolation frameworks were not in use. As a result, a standard pediatric program had initially been proposed requiring two relatively large placebo-controlled pivotal trials. However, as experience with the use of secukinumab grew, so did experience with - and regulatory openness to - innovative quantitative approaches such as extrapolation. It became clear that the pediatric development of secukinumab could be substantially accelerated by these novel ideas. Here we report how these concepts were implemented in the pediatric development program of secukinumab in psoriasis, using a wide range of innovative quantitative techniques. This strategy led to the removal of the placebo arm from one trial, a substantial reduction of the overall sample size in this program, and a significantly faster approval of secukinumab for the pediatric psoriasis population.

Precision Reimbursement for Precision Medicine: Using Real-World Evidence to Evolve From Trial-and-Project to Track-and-Pay to Learn-and-Predict

Basic scientists and drug developers are accelerating innovations toward the goal of precision medicine. Regulators create pathways for timely patient access to precision medicines, including individualized therapies. Healthcare payors acknowledge the need for change but downstream innovation for coverage and reimbursement is only haltingly occurring. Performance uncertainty, high price‐tags, payment timing, and actuarial risk issues associated with precision medicines present novel financial challenges for payors. With traditional drug reimbursement frameworks, payment is based on an assumed randomized controlled trial (RCT) projection of real‐world effectiveness, a “trial‐and‐project” strategy; the clinical benefit realized for patients is not usually ascertained ex post by collection of real‐world data (RWD). To mitigate financial risks resulting from clinical performance uncertainty, manufacturers and payors devised “track‐and‐pay” frameworks (i.e., the tracking of a pre‐agreed treatment outcome which is linked to financial consequences). Whereas some track‐and‐pay arrangements have been successful, inherent weaknesses include the potential for misalignment of incentives, the risk of channeling of patients, and a failure to use the RWD generated to enable continuous learning about treatments. “Precision reimbursement” (PR) intends to overcome inherent weaknesses of simple track‐and‐pay schemes. In combining the collection of RWD with advanced analytics (e.g., artificial intelligence and machine learning) to generate actionable real‐world evidence, with prospective alignment of incentives across all stakeholders (including providers and patients), and with pre‐agreed use and dissemination of information generated, PR becomes a “learn‐and‐predict” model of payment for performance. We here describe in detail the concept of PR and lay out the next steps to make it a reality.

Unmet Medical Need as a Driver for Pharmaceutical Sciences - A Survey Among Scientists

Historical antecedents of pharmaceutical sciences are sound on product orientation based on (analytical) chemistry, drug delivery and basic pharmacology. Over the last decades we have seen a transition towards a stronger disease orientation. This raises questions on whether, how and to what extent unmet medical need (UMN) is important in priority setting, funding and impact in pharmaceutical sciences. An online survey in 2020 collected perspectives of internationally recognised pharmaceutical scientists (N = 92), mainly from academia and industry, on drivers and influencing factors in pharmaceutical sciences. The study offers a unique global perspective, demonstrating a solid command of the global needs in pharmaceutical sciences. The survey revealed that UMN is currently seen as one of the three most important drivers, also in addition to emerging trends in science and opportunities driven by collaboration. There are expectations that UMN's impact becomes more influential. This was consistent for both industry and academic respondents. The majority of respondents also indicated that anticipated lessons learned from COVID-19 will strengthen the impact of UMN on science and leadership. This is important as prioritisation of research towards UMN can address the clinical needs where needed the most.

A Framework for Methodological Choice and Evidence Assessment for Studies Using External Comparators from Real-World Data

Several approaches have been proposed recently to accelerate the pathway from drug discovery to patient access. These include novel designs such as using controls external to the clinical trial where standard randomised controls are not feasible. In parallel, there has been rapid growth in the application of routinely collected healthcare ‘real-world’ data for post-market safety and effectiveness studies. Thus, using real-world data to establish an external comparator arm in clinical trials is a natural next step. Regulatory authorities have begun to endorse the use of external comparators in certain circumstances, with some positive outcomes for new drug approvals. Given the potential to introduce bias associated with observational studies, there is a need for recommendations on how external comparators should be best used. In this article, we propose an evaluation framework for real-world data external comparator studies that enables full assessment of available evidence and related bias. We define the principle of exchangeability and discuss the applicability of criteria described by Pocock for consideration of the exchangeability of the external and trial populations. We explore how trial designs using real-world data external comparators fit within the evidence hierarchy and propose a four-step process for good conduct of external comparator studies. This process is intended to maximise the quality of evidence based on careful study design and the combination of covariate balancing, bias analysis and combining outcomes.

Integrating Real-World Evidence in the Regulatory Decision-Making Process: A Systematic Analysis of Experiences in the US, EU, and China Using a Logic Model

Real world evidence (RWE) and real-world data (RWD) are drawing ever-increasing attention in the pharmaceutical industry and drug regulatory authorities (DRAs) all over the world due to their paramount role in supporting drug development and regulatory decision making. However, there is little systematic documentary analysis about how RWE was integrated for the use by the DRAs in evaluating new treatment approaches and monitoring post-market safety. This study aimed to analyze and discuss the integration of RWE into regulatory decision-making process from the perspective of DRAs. Different development strategies to develop and adopt RWE by the DRAs in the US, Europe, and China were reviewed and compared, and the challenges encountered were discussed. It was found that different strategies on development of RWE were applied by FDA, EMA, and NMPA. The extent to which RWE was adopted in China was relatively limited compared to that in the US and EU, which was highly related to the national pharmaceutical environment and development stages. A better understanding of the overall goals, inputs, activities, outputs, and outcomes in developing RWE will help inform actions to harness RWD and leverage RWE for better health care decisions.

Regulatory density as a means to refine current regulatory approaches for increasingly complex medicines

The continuous scientific, societal, and technological advancements have shifted drug development toward increasingly complex and ever more targeted treatments. This creates new and unprecedented challenges for global regulatory systems. To address the increased risks and uncertainties of increasingly complex medicine, we advocate for a more tailored and flexible regulatory approach, which is explained here with the concept of 'regulatory density'. In the context of this paper, 'regulatory density' describes the relative amount of obligatory standards, measures and procedures applied to certain medicinal products or product classes and the resources required to meet these requirements. Given that risk and uncertainty are dynamic variables that can change over time, with this paper, we want to stimulate (re)thinking of regulatory approaches for managing the challenges of future complex medicines.

Global regulatory progress in delivering on the promise of gene therapies for unmet medical needs

The rapid expansion of the gene therapy pipeline in recent years offers significant potential to treat diseases with great unmet medical need. However, the unique nature of these therapies poses challenges to regulating them within traditional frameworks, even when developing in a single country. Various factors exacerbate the issues in commercializing products across regions, including the lack of established regulatory frameworks for developing gene therapy products in many jurisdictions. While some countries have established separate regulatory frameworks for advanced therapies/regenerative medicine products, differences exist between them. Recommended solutions to overcome these hurdles include fostering convergence among countries with separate regulatory frameworks for these products and utilizing reliance and recognition for countries without such frameworks. Additionally, regulators who choose to establish new dedicated frameworks for regulating gene therapies should consider the inclusion of key elements such as expedited regulatory pathways that offer early engagement with regulators, innovative clinical trial design, and adequate post-market confirmatory studies. Increasing the alignment of regulatory pathways across countries will be crucial to facilitating the development of, and access to, gene therapies on a global scale.

A Comparative Study for License Application Regulations on Proprietary Chinese Medicines in Hong Kong and Canada

Ethnopharmacological Relevance: Chinese Medicine plays a symbolic role among traditional medicines. As Chinese Medicine products are widely used around the globe, regulations for Chinese Medicine products are often used as models for the efficient regulation of natural products that are safe, and high-quality.

Aim of the Study: We aimed to compare the regulatory registration requirements for Proprietary Chinese Medicines in Hong Kong and Canada.

Materials and Methods: We compared registration requirements for Proprietary Chinese Medicine in Hong Kong and Canada based on publicly available information provided by the respective Regulators. A marketed product, Zhizhu Kuanzhong Capsule (SFDA approval number Z20020003; NPN approval number 80104354), was used as a case study to demonstrate the similarities and differences of the requirements in both Hong Kong and Canada.

Results: There were similarities and differences between the two regulatory systems in terms of the quality, safety and efficacy requirements. Despite the superficial appearance of similar categories and groups/classes, Hong Kong requires significantly more primary test data compared to Canada's reliance on attestation to manufacturing according the standards outlined in approved reference pharmacopeias/texts.

Conclusion: Improved understand of the similarity and differences will enable applicants to plan appropriate strategies for gaining product approval. Exploring ways to harmonize the regulatory process has the potential to benefit manufacturers, regulators, and patients by increasing efficiency and decreasing costs.

The concept of justifiable healthcare and how big data can help us to achieve it

Over the last decades, the face of health care has changed dramatically, with big improvements in what is technically feasible. However, there are indicators that the current approach to evaluating evidence in health care is not holistic and hence in the long run, health care will not be sustainable. New conceptual and normative frameworks for the evaluation of health care need to be developed and investigated. The current paper presents a novel framework of justifiable health care and explores how the use of artificial intelligence and big data can contribute to achieving the goals of this framework.

Clinical Translation of Cell Therapies in Stroke (CT2S) Checklist-a pragmatic tool to accelerate development of cell therapy products

BACKGROUND

Cell therapies present an exciting potential but there is a long history of expensive translational failures in stroke research. Researchers engaged in cell therapy research would benefit from a practical framework that can help in planning research and development of investigational cell therapies into viable medical products.

METHODS

We developed a checklist using a mixed methodology approach to evaluate the impact of study design, regulatory policy, ethical, and health economic considerations for efficient implementation of early phase cell therapy studies.

RESULTS

The checklist comprises a series of questions arranged under four domains: the first concerns study design such as characterization of target study population, trial design, endpoints and operational fit of dosage, time, and route of administration to target populations. A second domain addresses the data package required for regulatory approval relevant to the intended use (allogeneic/autologous; homologous/non-homologous; nature of cell processing). The third domain comprises patient involvement to ensure relevant data is collected via targeted study design. The final domain requires the team to determine the critical data elements that could be built into study design to enable health economic data collection to be started at an early phase of the study.

CONCLUSIONS

The CT2S checklist can help to determine areas of expertise gaps and enable research groups to appropriately allocate resources for capacity building. Use of this checklist will allow identification of key areas where trial planning needs to be optimized, as well as helping to identify resources that need to be secured. The CT2S checklist can also serve as a general cell therapy research decision aid to improve research output and accelerate new cell therapy development.

Developments in evidence creation for treatments of inborn errors of metabolism

Inborn errors of metabolism (IEM) represent the first group of genetic disorders, amenable to causal therapies. In addition to traditional medical diet and cofactor treatments, new treatment strategies such as enzyme replacement and small molecule therapies, solid organ transplantation, and cell-and gene-based therapies have become available. Inherent to the rare nature of the single conditions, generating high-quality evidence for these treatments in clinical trials and under real-world conditions has been challenging. Guidelines developed with standardized methodologies have contributed to improve the practice of care and long-term clinical outcomes. Adaptive trial designs allow for changes in sample size, group allocation and trial duration as the trial proceeds. n-of-1 studies may be used in small sample sized when participants are clinically heterogeneous. Multicenter observational and registry-based clinical trials are promoted via international research networks. Core outcome and standard data element sets will enhance comparative analysis of clinical trials and observational studies. Patient-centered outcome-research as well as patient-led research initiatives will further accelerate the development of therapies for IEM.

Uncertainty tolerance among experts involved in drug reimbursement recommendations: Qualitative evidence from HTA committees in Canada and Poland

OBJECTIVES

Drug reimbursement decisions often rely on health technology assessment (HTA). Increasingly, new drugs have limited clinical evidence and uncertain clinical benefit. Our goal was to describe how members of drug advisory committees and other stakeholders conceptualize and tolerate uncertainty and how they rationalize uncertainty tolerance.

METHODS

Our triangulated parallel design applied two qualitative methods. We interviewed 31 members of drug advisory committees in Canada and Poland about their information needs and included hypothetical scenarios with uncertain clinical benefits. Respondents speculated about their likely reimbursement recommendation. We analyzed written recommendations of the pan Canadian Oncology Drug Review for drugs with uncertain benefit and compared initial recommendations to the responses from patient and clinician groups.

RESULTS

Uncertainty tolerance varied among committee members and across jurisdictions. In the scenario analysis, 7 Canadian and 11 Polish respondents leaned against recommending a hypothetical drug with uncertain clinical benefit, whereas 5 Canadian and 5 Polish respondents leaned in favour. Those against rationalized that uncertainty increases potential harm; those in favour rationalized that patients often have no alternatives. The document analysis revealed that patients had higher uncertainty tolerance in general.

CONCLUSIONS

Uncertainty tolerance varies among committee members and other stakeholders depending on their backgrounds and on the decision contexts. We argue that policy guidance around uncertainty management could improve the transparency and consistency of recommendations.

Improving Interactions Between Health Technology Assessment Bodies and Regulatory Agencies: A Systematic Review and Cross-Sectional Survey on Processes, Progress, Outcomes, and Challenges

The need to optimize drug development and facilitate faster access for patients has ignited discussions around the importance of improving interactions between health technology assessment (HTA) bodies and regulatory agencies. In this study, we conducted a systematic review to examine processes, progress, outcomes, and challenges of harmonization/interaction initiatives between HTA bodies and regulatory agencies. MEDLINE, EMBASE, and the International Pharmaceutical Abstracts database were searched up to 21 October 2019. Searches for gray literature (working papers, commissioned reports, policy documents, etc.) were performed via Google scholar and several institutional websites. An online cross-sectional survey was also conducted among HTA (n = 22) and regulatory agencies (n = 6) across Europe to supplement the systematic review. Overall, we found that while there are areas of divergence, there has been progress over time in narrowing the gap in evidentiary requirements for HTA bodies and regulatory agencies. Most regulatory agencies (4/6; 67%) and half (11/22, 50%) of the HTA bodies reported having a formal link for “collaborating” with the other. Several mechanisms such as early tripartite dialogues, parallel submissions (reviews), adaptive licensing pathways, and postauthorization data generation have been explored as avenues for improving collaboration. A number of pilot initiatives have shown positive effects of these models to reduce the time between regulatory and HTA decisions, which may translate into faster access for patients to life-saving therapies. Thus, future approaches aimed at improving harmonization/interaction between HTA bodies and regulatory agencies should build on these existing models/mechanisms while examining their long-term impacts. Several barriers including legal, organizational, and resource-related factors were also identified, and these need to be addressed to achieve greater alignment in the current regulatory and reimbursement landscape.

Regenerative medicine regulatory policies: A systematic review and international comparison

BACKGROUND

A small number of regenerative medicines (RMs) have received market authorization (MA) worldwide, relative to the large number of clinical trials currently being conducted. Regulatory issues constitute one major challenge for the MA of RMs.

OBJECTIVE

This study aimed to systematically review the regulation of RMs internationally, to identify the regulatory pathways for approved RMs, and to detail expedited programs to stimulate MA process.

METHODS

Official websites of regulatory authorities in 9 countries (United States (US), Japan, South Korea, Australia, Canada, New Zealand, Singapore, China, and India) and the European Union (EU) were systematically browsed, and was complemented by a systematic literature review in Medline and Embase database.

RESULTS

Specific RM legislation/frameworks were available in the EU, US, Japan, South Korea and Australia. A risk-based approach exempting eligible RMs from MA regulations were adopted in the EU and 6 countries. All investigated regions have established accelerated review or approval programs to facilitate the MA of RMs. 55 RMs have received MA in 9 countries and the EU. Twenty-three RMs received Priority Medicine designation, 32 RMs received Regenerative Medicine Advanced Therapy designation, and 11 RMs received SAKIGAKE (fore-runner initiative) designation.

CONCLUSION

Regulators have adopted proactive strategies to facilitate RM approval. However, addressing the discrepancies in regulatory requirements internationally remains challenging.

Decision Making Under Uncertainty: Comparing Regulatory and Health Technology Assessment Reviews of Medicines in the United States and Europe

Assessments of clinical evidence vary between regulators and health technology assessment bodies, but precise differences remain unclear. To compare uncertainties raised on the clinical evidence of approved drugs, we analyzed assessments of regulators and health technology assessment (HTA) bodies in the United States and Europe. We found that US and European regulators report uncertainties related to safety for almost all drugs (85–94%), whereas HTA bodies reported these less (53–59%). By contrast, HTA bodies raised uncertainties related to effects against relevant comparators for almost all drugs (88–100%), whereas this was infrequently addressed by regulators (12–32%). Regulators as well as HTA bodies reported uncertainties related to the patient population for 60–95% of drugs. The patterns of regulator‐HTA misalignment were comparable between the United States and Europe. Our results indicate that increased coordination between these complementary organizations is necessary to facilitate the collection of necessary evidence in an efficient and timely manner.

The development of complex and controversial innovations. Genetically modified mosquitoes for malaria eradication

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Using the example of mosquitoes that are genetically modified for malaria eradication through gene drive methods, a scientifically complex ‘living technology’, we show how complexity, uncertainty and risk can propel NPD processes towards a linear sequence of stages.

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Although the need to control risks associated with gene drive technology imposes linearity to the NPD process, there are possibilities for deviation from a structured sequence of stages. This is due to the effects of feedback loops in the wider system of evidence creation and learning at the population and governance levels, which cumulatively impact on acceptance of the innovation.

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The NPD and adoption processes involved in the use of gene drive technology are closely intertwined, and the endpoint for R&D and beginning of ‘mainstream’ adoption and diffusion are unclear.

When there is significant uncertainty in an innovation project, research literature suggests that strictly sequencing actions and stages may not be an appropriate mode of project management. We use a longitudinal process approach and qualitative system dynamics modelling to study the development of genetically modified (GM) mosquitoes for malaria eradication in an African country. Our data were collected in real time, from early scientific research to deployment of the first prototype mosquitoes in the field. The 'gene drive' technology for modifying the mosquitoes is highly complex and controversial due to risks associated with its characteristics as a living, self-replicating technology. We show that in this case the innovation journey is linear and highly structured, but also embedded within a wider system of adoption that displays emergent behaviour. Although the need to control risks associated with the technology imposes a linearity to the NPD process, there are possibilities for deviation from a more structured sequence of stages. This arises from the effects of feedback loops in the wider system of evidence creation and learning at the population and governance levels, which cumulatively impact on acceptance of the innovation. The NPD and adoption processes are therefore closely intertwined, meaning that the endpoint for R&D and beginning of 'mainstream' adoption and diffusion are unclear. A key challenge for those responsible for NPD and its regulation is to plan for the adoption of the technology while simultaneously conducting its scientific and technical development.

Views of European Drug Development Stakeholders on Treatment Optimization and Its Potential for Use in Decision-Making

Background

The current drug development paradigm has been criticized for being too drug-centered and for not adequately focusing on the patients who will eventually be administered the therapeutic interventions it generates. The drug-driven nature of the present framework has led to the emergence of a research gap between the pre-approval development of anticancer medicines and their post-registration use in real-life clinical practice. This gap could potentially be bridged by transitioning toward a patient-centered paradigm that places a strong emphasis on treatment optimization, which strives to optimize the way health technologies are applied in a real-world environment. However, questions remain concerning the ideal features of treatment optimization studies and their acceptability among key stakeholders.

Objectives

The aim of this study was to explore the views of key stakeholders in the drug development process regarding the concept of treatment optimization.

Methods

Semi-structured interviews were conducted between December 2018 and May 2019 with 26 participants across ten EU Member States and six different stakeholder groups, including academic clinicians as well as representatives of patient organizations, regulatory authorities, health technology assessment agencies, payers, and industry.

Results

Based on the input of the experts interviewed, clarification was obtained regarding the optimal features of treatment optimization studies in terms of their conduct, funding, timing, design, and setting. Moreover, a number of opportunities and challenges of undertaking such trials were identified. Inter-stakeholder discussion during their design was seen as desirable. There was also broad support among the participants for regulatory measures to facilitate treatment optimization, although there was no agreement on the optimal scale and nature of these initiatives. Furthermore, the interviewees believed that the evidence strength of well-designed treatment optimization studies performed according to rigorous quality standards is greater than or at least equal to that of classical clinical trials. In addition, there was a strong consensus that the results of treatment optimization studies should be taken into account during the decision-making of regulators, payers, and/or clinicians.

Conclusions

Stakeholders involved in drug development consider treatment optimization studies to be valuable tools to address current evidence gaps and support their implementation into the existing research framework.

"Stick or Twist?" Negotiating Price and Data in an Era of Conditional Approval

BACKGROUND

Changes in the regulatory context enable faster approval of transformative medicines. They also lead to health technology assessment (HTA) agencies having to make decisions with less evidence. In response, HTA agencies have also initiated forms of conditional approval. When the evidence base for a new oncology treatment leaves substantial uncertainty, the new Cancer Drugs Fund allows the National Institute for Heath and Care Excellence to give the manufacturer two options: (1) offer a low price based on conservative assumptions and obtain immediate approval ("stick") or (2) wait until the evidence base has further matured before finalizing a potentially higher agreed price ("twist").

OBJECTIVES

The purpose of this article is to explain how, using the theoretical framework of the expected value of sample information, simulation methods can help inform a manufacturer's decisions when faced with the option to stick or twist.

METHODS

We first summarize a general model to help frame the manufacturer's negotiating strategy. We then use a motivating case study, based on a hypothetical immunotherapy, to illustrate how manufacturers can use simulation methods to robustly characterize the uncertainty inherent to further data collection and incorporate this uncertainty within their decision making.

RESULTS

Our approach allows us to estimate the commercial value of generating additional data (the difference between the estimated net present value of stick and twist). We test the sensitivity of the results to different assumptions via scenario analyses.

CONCLUSIONS

This article shows that simulation methods can be used to help pharmaceutical managers make informed strategic decisions in contexts of uncertainty.

Affordability of oncology drugs: accuracy of budget impact estimations

Background: In many countries, Budget Impact (BI) informs reimbursement decisions. Evidence has shown that decision-makers have restricted access based on high BI estimates but studies show that BI estimates are often inaccurate. Objective: To assess the accuracy of BI estimations used for informing access decisions on oncology drugs in the Netherlands. Study Design: Oncology products for which European Medicines Agency Marketing Authorisation was granted between 1-1-2000 and 1-10-2017 were selected. Observed BI data were provided by FarmInform. BI estimates were extracted from the reimbursement dossiers of the Dutch Healthcare Institute. Products without an estimated BI in the reimbursement dossier were excluded. Accuracy is defined as the ratio observed BI/estimated BI. Setting: General community, the Netherlands. Results: Ten products were included in the base case analysis. Mean accuracy was 0.64 and observed BI deviated by more than 40% and 100% from the estimated BI for 4 and 5 products, respectively. For all products together, €141 million BI was estimated and €82 million BI was observed, a €59 million difference. Conclusions: The findings indicate that BI estimates for oncology drugs in the Netherlands are inaccurate. The role and use of BI in reimbursement decisions for these potentially life-saving drugs should therefore be considered carefully, as well as BI estimation methodology.

Achieving equal and timely access to innovative anticancer drugs in the European Union (EU): summary of a multidisciplinary CECOG-driven roundtable discussion with a focus on Eastern and South-Eastern EU countries

The Central European Cooperative Oncology Group (CECOG) and ‘ESMO Open—Cancer Horizons’ roundtable discussion brought together stakeholders from several European Union (EU) countries involved in drug development, drug authorisation and reimbursement or otherwise affected by delayed and unequal access to innovative anticancer drugs. The approval process of drugs is well established and access delays can be caused directly or indirectly by national or regional decision-making processes on reimbursement. The two key aspects for those involved in reimbursement decisions are first the level of evidence required to decide and second pricing, which can be challenging for some innovative oncology compounds, especially in Eastern and South-Eastern European countries. Other important factors include: available healthcare budget; the structure and sophistication of healthcare authorities and health technology assessment processes; societal context and political will. From the point of view of the pharmaceutical industry, better alignment between stakeholders in the process and adaptive pathway initiatives is desirable. Key aspects for patients are improved access to clinical trials, preapproval availability and reports on real-world evidence. Restricted access limits oncologists’ daily work in Eastern and South-Eastern EU countries. The roundtable discussion suggested considering the sequencing of regulatory approval and reimbursement decisions together with more flexible contracting as a possible way forward. The panel concluded that early and regular dialogue between all stakeholders including regulators, payers, patient stakeholders and industry is required to improve the situation.

Unmet Medical Need: An Introduction to Definitions and Stakeholder Perceptions

BACKGROUND

Despite increasing informal and formal use of unmet medical need (UMN) in drug development, regulation, and assessment, there is no insight into its definitions in use. This study aims to provide insight into the current definitions in use and to provide a starting point for a multi-stakeholder discussion on alignment.

METHODS

A scoping and a gray literature review were performed to locate definitions of UMN in literature and on stakeholder websites. These definitions were categorized and then discussed among the multi-stakeholder author group via semistructured group discussions and open session workshops with a broader stakeholder audience. Issues with the formation of a common definition and mechanisms for use were discussed.

RESULTS

The reviews yielded 16 definitions. Differences were evident, but all included 1 or more of the following elements: (adequacy of) available treatments (16 of 16: 100%), disease severity or burden (6 of 16: 38%), and patient population size (1 of 16: 6%). The stakeholder discussions led to a suggestion for a definition including the first 2 items and, depending on context, population size. The discussions also showed that quantification of UMN is highly dependent on the scope and the value framework in which it is used based on different stakeholder preferences and responsibilities.

CONCLUSION

We encourage stakeholders that want to promote alignment on the concept of UMN to prospectively discuss the scope in which they want to apply the concept, what elements they find important for consideration in each case, and how they would measure UMN within the broader regulatory or value framework applicable.

Group sequential adaptive designs in series of time-to-event randomised trials in rare diseases: A simulation study

In rare diseases, fully powered large trials may not be doable in a reasonable time frame even with international collaborations. In a previous work, we proposed an approach based on a series of smaller parallel group two-arm randomised controlled trials (RCT) performed over a long research horizon. Within the series of trials, the treatment selected after each trial becomes the control treatment of the next one. We concluded that running more trials with smaller sample sizes and relaxed α-levels leads in the long term and under reasonable assumptions to larger survival benefits with a moderate increase of risk as compared to traditional designs based on larger but fewer trials designed to meet stringent evidence criteria. We now extend this quantitative framework with more 'flexible' designs including interim analyses for futility and/or efficacy, and three-arm adaptive designs with treatment selection at interim. In the simulation study, we considered different disease severities, accrual rates, and hypotheses of how treatments improve over time. For each design, we estimated the long-term survival benefit as the relative difference in hazard rates between the end and the start of the research horizon, and the risk defined as the probability of selecting at the end of the research horizon a treatment inferior to the initial control. We assessed the impact of the α-level and the choice of the stopping rule on the operating characteristics. We also compared the performance of series based on two- vs. three-arm trials. We show that relaxing α-levels within the limit of 0.1 is associated with larger survival gains and moderate increase of risk which remains within acceptable ranges. Including an interim analysis with a futility rule is associated with an additional survival gain and a better risk control as compared to series with no interim analysis, when the α-level is below or equal to 0.1, whereas the benefit of including an interim analysis is rather small for higher α-levels. Including an interim analysis for efficacy yields almost no additional gain. Series based on three-arm trials are associated with a systematic improvement in terms of survival gain and risk control as compared to series of two-arm trials.

The Iterative Development of Medicines Through the European Medicine Agency's Adaptive Pathway Approach

The development of novel regulatory tools such as adaptive clinical trial design and utilization of real-world evidence are topics of high interest. Recently, the European Medicines Agency (EMA) introduced the Adaptive Pathways (AP) that represents an innovative tool in healthcare systems allowing the early dialogue with multiple stakeholders on promising and innovative medicinal products in areas with an high unmet medical need. The innovative aspect in the AP is the early involvement of several stakeholders such as pharmaceutical industry, the Academia, Health Technology Assessment (HTA) bodies, and patient representatives bringing their real experience with the disease and their expectations about the treatment. AP is not a new licensing tool but an opportunity for a very early discussions, before starting the phase II studies, among all stakeholders, including regulators, companies, HTA bodies, and patient representatives on a new potential medicine in areas of high unmet medical need. The aim of this paper is to describe the evolution of the AP approach from the beginning of the pilot project to date, highlighting major advances, and achievement at European level.

Challenges in Designing Clinical Trials to Test New Drugs in the Pregnant Woman and Fetus

The need for new drugs in pregnancy is widely recognized. This review identifies several unique challenges and describes some solutions. Specific studies and drug development programs need careful planning that accounts for the needs of regulatory agencies. The perinatal (obstetric/pediatric) community needs to establish collaborations to develop methodologies, to facilitate data sharing, and to lobby for research and access to medicines. There is a need to gather and present information that promotes proportionate judgments of the balance between potential benefits and risks. This will require researchers to look beyond their traditional ways of working.

Real-World Evidence Gathering in Oncology: The Need for a Biomedical Big Data Insight-Providing Federated Network

Moving toward new adaptive pathways for the development and access to innovative medicines implies that real-world data (RWD) collected throughout the medicinal product life cycle is becoming increasingly important. Big data analytics on RWD can obtain new and powerful insights into medicines' effectiveness. However, the healthcare ecosystem still faces many sector-specific challenges that hamper the use of big data analytics delivering real world evidence (RWE). We distinguish between exploratory (ExTE) and hypotheses-evaluating (HETE) studies testing treatment effectiveness in the real world. From our experience and in the context of the four V's of data management, we show that to get meaningful results data Variety and Veracity are needed regardless of the type of study conducted. More so, for ExTE studies high data Volume is needed while for HETE studies high Velocity becomes essential. Next, we highlight what are needed within the biomedical big data ecosystem, being: (a) international data reusability; (b) real-time RWD processing information systems; and (c) longitudinal RWD. Finally, in an effort to manage the four V's whilst respecting patient privacy laws we argue for the development of an underlying federated RWD infrastructure on a common data model, capable of bringing the centrally-conducted big data analysis to the de-centrally kept biomedical data.

Evaluating the Use of Nonrandomized Real-World Data Analyses for Regulatory Decision Making

The analysis of longitudinal healthcare data outside of highly controlled parallel-group randomized trials, termed real-world evidence (RWE), has received increasing attention in the medical literature. In this paper, we discuss the potential role of RWE in drug regulation with a focus on the analysis of healthcare databases. We present several cases in which RWE is already used and cases in which RWE could potentially support regulatory decision making. We summarize key issues that investigators and regulators should consider when designing or evaluating such studies, and we propose a structured process for implementing analyses that facilitates regulatory review. We evaluate the empirical evidence base supporting the validity, transparency, and reproducibility of RWE from analysis of healthcare databases and discuss the work that still needs to be done to ensure that such analyses can provide decision-ready evidence on the effectiveness and safety of treatments.

Comparative and combined effectiveness of innovative therapies in cancer: a literature review

To achieve therapeutic innovation in oncology, already expensive novel medicines are often concomitantly combined to potentially enhance effectiveness. While this aggravates the pricing problem, comparing effectiveness of novel yet expensive (concomitant) treatments is much needed for healthcare decision-making to deliver effective but affordable treatments. This study reviewed published clinical trials and real-world studies of targeted and immune therapies. In total, 48 studies compared and/or combined multiple novel products on breast, colorectal, lung and melanoma cancers. To a great extent, products evaluated in each study were owned by one manufacturer. However, cross-manufacturer assessments are also needed. Next to costs and intensive market competition, the absence of a regulatory framework enforcing real-world multiproduct studies prevents these from being conducted. Trusted third parties could facilitate such real-world studies, for which appropriate and efficient data access is needed.

A framework for monitoring of new drugs in Sweden

In order to monitor the net public health benefit of new drugs, especially in the light of recent stepwise approval approaches, there is a need to optimize real-time post-marketing evaluation of new drugs using data collected in routine care. Sweden, with its unique possibilities for observational research, can provide these data. We herein propose a framework for continuous monitoring of the effectiveness, safety, and cost-effectiveness of new drugs, using prospectively determined protocols designed in collaboration between all relevant stakeholders. We believe that this framework can be a useful tool for healthcare authorities and reimbursement agencies in the introduction of new drugs.

Weighing of Evidence by Health Technology Assessment Bodies: Retrospective Study of Reimbursement Recommendations for Conditionally Approved Drugs

This study assessed whether five Health Technology Assessment (HTA) bodies in Europe were more negative about drugs with a Conditional Marketing Authorization (CMA) that are approved without controlled studies compared to CMA drugs that are approved based on controlled studies. The HTA recommendations were categorized into positive, restricted, and negative. A total of 92 HTA recommendations were available for 27 drugs. Thirty of 62 (48%) and 17 of 30 (57%) of the recommendations were negative for drugs with and without controlled studies, respectively. Overall, only 12 (13%) recommendations were positive. In all jurisdictions, recommendations between drugs with and drugs without controlled data were comparable, which suggests that the presence of controlled data is not decisive in HTA evaluations. The small proportion of unrestricted positive recommendations highlights difficulties with recommending the drugs in this cohort, which may be caused by scientific uncertainty or other factors. Earlier collaboration between stakeholders is advised in order to improve patient access.

Medicines Adaptive Pathways to Patients: Why, When, and How to Engage?

Medicines Adaptive Pathways to Patients (MAPPs) seeks to foster access to novel beneficial treatments for the right patient groups at the earliest appropriate time in the product life-span, in a sustainable fashion. We summarize the MAPPs engagement process and critical questions to be asked at each milestone of the product life-span. These considerations are of relevance for regulatory and access pathways that strive to address the "evidence vs. access" conundrum.