scholarly journals The New FDA Real-World Evidence Program to Support Development of Drugs and Biologics

2019 ◽  
Vol 14 (2) ◽  
pp. 345-349 ◽  
Author(s):  
David C. Klonoff
Keyword(s):  
Real World ◽  
Stakeholder Engagement ◽  
Medical Community ◽  
Real World Data ◽  
The Public ◽  
Public Meetings ◽  
Real World Evidence ◽  
Guidance Documents ◽  
Approved Drugs ◽  
Regulatory Decisions

FDA has launched a Real World Evidence (RWE) Program for using real-world evidence (RWE) to help support new indications for already approved drugs or biologics and postapproval studies. The plan also includes stakeholder engagement efforts, demonstration projects, leadership activities, and development of guidance documents to assist developers interested in using real-world data (RWD) to develop RWE to support FDA regulatory decisions. This plan was mandated by the Cures Act passed in 2016. Over the 24-month period from passage of the law until FDA officially announced their program, FDA has gone to considerable efforts to educate the public about the benefits of RWE and encourage researchers to consider situations where RWE trials can generate useful information. Through a variety of stakeholder engagement projects, including publication of articles in medical journals, participation in public meetings, and development of initiatives, FDA has put more effort into preparing the medical community for its new emphasis on RWE than any other new policy that I can recall.

scholarly journals Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data

2020 ◽  
Vol 9 (3) ◽  
pp. 155-159
Author(s):  
Michael J Seewald ◽  
Jonathan M Plumb ◽  
Ben Gutierrez ◽  
Johan Liwing ◽  
Maurille Feudjo Tepie ◽  
...  
Keyword(s):  
Real World ◽  
White Paper ◽  
Medical Community ◽  
Real World Data ◽  
World Data ◽  
Real World Evidence ◽  
Challenges And Opportunities

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the ‘RWE Leadership Forum’: a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

scholarly journals Real-World Evidence Should Be Used in Regulatory Decisions About New Pharmaceutical and Medical Device Products for Diabetes

2019 ◽  
Vol 13 (6) ◽  
pp. 995-1000 ◽  
Author(s):  
David C. Klonoff ◽  
Alberto Gutierrez ◽  
Alexander Fleming ◽  
David Kerr
Keyword(s):  
Real World ◽  
Randomized Clinical Trials ◽  
Sole Source ◽  
Real World Data ◽  
Pharmacy Records ◽  
Health Records ◽  
Additional Information ◽  
Real World Evidence ◽  
Combining Data ◽  
Regulatory Decisions

Randomized clinical trials (RCTs) are no longer the sole source of data to inform guidelines, regulatory, and policy decisions. Real-world data (RWD), collected from registries, electronic health records, insurance claims, pharmacy records, social media, and sensor outputs from devices form real-world evidence (RWE), which can supplement evidence from RCTs. Benefits of using RWE include less time and cost to produce meaningful data; the ability to capture additional information, including social determinants of health that can impact health outcomes; detection of uncommon adverse events; and the potential to apply machine learning and artificial intelligence to the delivery of health care. Overall, combining data from RCTs and RWE would allow regulators to make ongoing and more evidence-based decisions in approving and monitoring products for diabetes.

scholarly journals Real-world evidence: perspectives on challenges, value, and alignment of regulatory and national health technology assessment data collection requirements

2021 ◽  
Vol 37 ◽  
Author(s):  
Hannah Sievers ◽  
Angelika Joos ◽  
Mickaël Hiligsmann
Keyword(s):  
Health Technology Assessment ◽  
Technology Assessment ◽  
Real World ◽  
Health Technology ◽  
Practical Experience ◽  
Added Value ◽  
Real World Data ◽  
Conflicting Demands ◽  
Real World Evidence ◽  
Semistructured Interviews

Abstract Objective This study aims to assess stakeholder perceptions on the challenges and value of real-world evidence (RWE) post approval, the differences in regulatory and health technology assessment (HTA) real-world data (RWD) collection requirements under the German regulation for more safety in drug supply (GSAV), and future alignment opportunities to create a complementary framework for postapproval RWE requirements. Methods Eleven semistructured interviews were conducted purposively with pharmaceutical industry experts, regulatory authorities, health technology assessment bodies (HTAbs), and academia. The interview questions focused on the role of RWE post approval, the added value and challenges of RWE, the most important requirements for RWD collection, experience with registries as a source of RWD, perceptions on the GSAV law, RWE requirements in other countries, and the differences between regulatory and HTA requirements and alignment opportunities. The interviews were recorded, transcribed, and translated for coding in Nvivo to summarize the findings. Results All experts agree that RWE could close evidence gaps by showing the actual value of medicines in patients under real-world conditions. However, experts acknowledged certain challenges such as: (i) heterogeneous perspectives and differences in outcome measures for RWE generation and (ii) missing practical experience with RWD collected through mandatory registries within the German benefit assessment due to an unclear implementation of the GSAV. Conclusions This study revealed that all stakeholder groups recognize the added value of RWE but experience conflicting demands for RWD collection. Harmonizing requirements can be achieved through common postlicensing evidence generation (PLEG) plans and joint scientific advice to address uncertainties regarding evidence needs and to optimize drug development.

scholarly journals Generating real-world evidence from unstructured clinical notes to examine clinical utility of genetic tests: use case in BRCAness

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yiqing Zhao ◽  
Saravut J. Weroha ◽  
Ellen L. Goode ◽  
Hongfang Liu ◽  
Chen Wang
Keyword(s):  
Targeted Therapy ◽  
Data Quality ◽  
Real World ◽  
Genetic Information ◽  
Genetic Data ◽  
Real World Data ◽  
Rule Based ◽  
Clinical Notes ◽  
Real World Evidence ◽  
F Measure

Abstract Background Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in the clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients’ genetic information and further associate treatment decisions with genetic information. Methods We proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated in a Foundation-tested women cancer cohort (N = 196). Upon retrieval of patients’ genetic information using NLP system, we assessed the completeness of genetic data captured in unstructured clinical notes according to a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients’ treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy. Results We identified seven topics in the clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance. Our rule-based system achieved a precision of 0.87, recall of 0.93 and F-measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F-measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F-measure of 0.82 for seven-topic classification. We found in result-containing sentences, the capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies. Conclusions In conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes. Data quality issues such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate the real-world utility of genetic information to initiate a prescription of targeted therapy.

PP205 The Use Of Real-World Evidence To Support National Institute For Health And Care Excellence Medical Technology Submissions

2021 ◽  
Vol 37 (S1) ◽  
pp. 26-26
Author(s):  
Scott Gibson ◽  
Sita Saunders ◽  
Maximilian Blüher ◽  
Amanda Hansson Hedblom ◽  
Rafael Torrejon Torres ◽  
...  
Keyword(s):  
Decision Making ◽  
Real World ◽  
Trial Design ◽  
Clinical Evidence ◽  
Patient Characteristics ◽  
The United Kingdom ◽  
Real World Evidence ◽  
Guidance Documents ◽  
Meta Analyses ◽  
Positive Recommendation

IntroductionAlthough randomized controlled trials (RCTs) are recognized as providing the highest level of clinical evidence, few medical device RCTs are available due to underfunding or inherent challenges associated with trial design. This study examines the extent to which real-world evidence (RWE) supports the recommendations made by the National Institute for Health and Care Excellence Medical Technologies Evaluation Programme (MTEP).MethodsAll MTEP guidance documents published online prior to October 2020 were reviewed. The “case for adoption” recommendation, type of clinical data, and clinical critiques for each MTEP submission were extracted and categorized. RWE was defined as studies with neither blinding nor prospective selection or control of patient characteristics.ResultsOf the MTEP submissions reviewed, 34 of 45 (76%) received a positive recommendation. Independent of outcome, all submissions included RWE, but only 19 (42%) utilized RCT evidence (15 were recommended and four were not). Meta-analyses of RWE were used whenever possible. The most common clinical critiques in unsuccessful submissions were the following: (i) not generalizable to the United Kingdom National Health Service (NHS); (ii) low quality; (iii) likelihood of bias; (iv) trial design faults; (v) uncertain benefit; and (vi) evidence unrelated to scope.ConclusionsThis study suggests that while the use of RCTs has not always led to a positive recommendation, RWE can be valuable in decision-making. Evidence that is generalizable to the NHS, is related to the scope, and shows clear indication of benefit is more likely to positively influence MTEP decision-making.

scholarly journals Disease Network Delineates the Disease Progression Profile of Cardiovascular Diseases

2020 ◽  
Author(s):  
Zefang Tang ◽  
Yiqin Yu ◽  
Kenney Ng ◽  
Daby Sow ◽  
Jianying Hu ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Disease Progression ◽  
Real World ◽  
Disease Risk ◽  
Disease Network ◽  
Real World Data ◽  
Risk Models ◽  
Age Bias ◽  
Real World Evidence ◽  
Tremendous Amount

AbstractAs Electronic Health Records (EHR) data accumulated explosively in recent years, the tremendous amount of patient clinical data provided opportunities to discover real world evidence. In this study, a graphical disease network, named progressive cardiovascular disease network (progCDN), was built based on EHR data from 14.3 million patients 1 to delineate the progression profiles of cardiovascular diseases (CVD). The network depicted the dominant diseases in CVD development, such as the heart failure and coronary arteriosclerosis. Novel progression relationships were also discovered, such as the progression path from long QT syndrome to major depression. In addition, three age-group progCDNs identified a series of age-associated disease progression paths and important successor diseases with age bias. Furthermore, we extracted a list of salient features to build a series of disease risk models based on the progression pairs in the disease network. The progCDN network can be further used to validate or explore novel disease relationships in real world data. Features with sufficient abundance and high correlation can be widely applied to train disease risk models when using EHR data.

scholarly journals Development of an Innovative Real-World Evidence Registry for the Herpes Simplex Virus: Case Study

10.2196/16933 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e16933 ◽  
Author(s):  
Michelle Helena van Velthoven ◽  
Ching Lam ◽  
Caroline de Cock ◽  
Terese Stenfors ◽  
Hassan Chaudhury ◽  
...  
Keyword(s):  
Herpes Simplex Virus ◽  
Herpes Simplex ◽  
Real World ◽  
Physical Symptoms ◽  
Use Cases ◽  
Real World Data ◽  
World Data ◽  
Real World Evidence ◽  
Simplex Virus

Background Infection with the herpes simplex virus (HSV) is common but not well understood. Furthermore, there remains a social stigma surrounding HSV that can have psychosocial implications for those infected. Despite many patients infected with HSV experiencing mild-to-severe physical symptoms, only one subeffective treatment is available. A registry collecting real-world data reported by individuals potentially infected with HSV could help patients to better understand and manage their condition. Objective This study aimed to report on the development of a registry to collect real-world data reported by people who might be infected with HSV. Methods A case study design was selected as it provides a systematic and in-depth approach to investigating the planning phase of the registry. The case study followed seven stages: plan, design, prepare, collect, analyze, create, and share. We carried out semistructured interviews with experts, which were thematically analyzed and used to build use cases for the proposed registry. These use cases will be used to generate detailed models of how a real-world evidence registry might be perceived and used by different users. Results The following key themes were identified in the interviews: (1) stigma and anonymity, (2) selection bias, (3) understanding treatment and outcome gaps, (4) lifestyle factors, (5) individualized versus population-level data, and (6) severe complications of HSV. We developed use cases for different types of users of the registry, including individuals with HSV, members of the public, researchers, and clinicians. Conclusions This case study revealed key considerations and insights for the development of an appropriate registry to collect real-world data reported by people who might be infected with HSV. Further development and testing of the registry with different users is required. The registry must also be evaluated for the feasibility and effectiveness of collecting data to support symptom management. This registry has the potential to contribute to the development of vaccines and treatments and provide insights into the impact of HSV on other conditions.

scholarly journals Generating Real-World Evidence from Unstructured Clinical Notes to Examine Clinical Utility of Genetic Tests: Use Case in BRCAness

2020 ◽  
Author(s):  
Yiqing ZHAO ◽  
Saravut J Weroha ◽  
Ellen Goode ◽  
Hongfang Liu ◽  
Chen Wang
Keyword(s):  
Targeted Therapy ◽  
Data Quality ◽  
Real World ◽  
Genetic Information ◽  
Genetic Data ◽  
Real World Data ◽  
Rule Based ◽  
Clinical Notes ◽  
Real World Evidence ◽  
F Measure

Abstract Background: Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients’ genetic information and further associate treatment decisions with genetic information.Methods: We proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated on a Foundation-tested women cancer cohort (N=196). Upon retrieval of patients’ genetic information using NLP system, we assessed completeness of genetic data captured in unstructured clinical notes according a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients’ treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy. Results: We identified seven topics in clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance (VUS). Our rule-based system achieved a precision of 0.87, recall of 0.93 and F-measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F-measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F-measure of 0.82 for seven-topic classification. We found in result-containing sentences, capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies.Conclusions: In conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes. Data quality issue such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate real-world utility of genetic information to initiate prescription of targeted therapy.

Sign in / Sign up

Export Citation Format

Share Document