What are the new developments and opportunities in the RWE use case in 2020?

For future-oriented people who aspire to make a difference in the biopharmaceutical industry, it is critical to understand and predict trends affecting healthcare decisions in a rapidly changing environmentSyneos Health ® Insights Hub recently released the Healthcare Industry Trends 2020 reportThe report brings together the views of hundreds of experts working in the biopharmaceutical industryWe'll cover the health care industry trends detailed in the report in a separate sectionin the coming 2020, it's critical to understand how people respond to therapeutic drugs in the complex real worldFrom building organizations' in-depth knowledge of real-world evidence (RWE) to learning new ways to inject data into clinical trial design, the pharmaceutical industry leader is helping his team continue to demonstrate and demonstrate the industry's impact beyond regulatory requirements and payer expectationsthese new areas, there is no room for negotiation
and over the past few years, pharmaceutical companies have seen, to a large extent, the steady value RWE creates for patients and stakeholdersMost pharmaceutical industry leaders believe this is a key success factor in the acquisition and adoption of new treatmentsA growing number of healthcare decision makers recognize that, without exception, RWes based on outcome data need to be considered, in addition to traditional safety and efficacy measures, whether payers, health care providers, patient advocacy groups, clinical guidelines makers, or regulatorscomprehensive organizational change remains the biggest challenge facing the pharmaceutical industryThe front-runners are working hard to get everyone in the company in the company to agree on RWEThis fundamental problem, if not addressed properly, could hinder the company's ability to develop a strong RWE research agenda, undermine the ability to advance within the organization, and thus seriously hamper efforts to successfully introduce new therapiescompanies that have not yet achieved a broad and in-depth understanding of RWE, may face three challenges in the coming year:data sources: Resources, and the Drug Mingconde Content Team Mappingonce these challenges are overcome, the companies concerned will begin to see the next key shift: timingIn order to obtain a highly selective set of prescriptions, real-world data collection began in Phase 1 clinically, which became even more important By 2020, payers will have higher expectations for integrated data than ever before Pharmaceutical companies are gaining insight into new methods of data collection and the new regulatory guardrail around RWE In 2008, for example, the FDA implemented the sharing of pre-approval data with crowd-based decision makers, but not all organizations have learned how to integrate that data into their internal guidelines and systems In addition to clinical trials, payers have implemented more stringent evidentiary requirements that need to be overcome, such as conditional reimbursement so, in 2020, an in-depth understanding of real-world evidence across the organization will be a priority for the pharmaceutical industry fewer patients involved in clinical trials synthetic clinical trials, considered to be modern retrospective studies, and the development of synthetic clinical trials offers more possibilities for fewer patients to participate in clinical trials from electronic medical records (HER) to data integrators to empowering patients to collect their own data, there has been a surge in the number of de-identified patient data In addition to de-identifying patient data, there are all unused, detailed aggregatedata from large clinical trials In the new decade, innovators are increasingly conducting synthetic clinical trials to make the most of these data Using existing data to capture RWE's synthetic clinical trials can be seen as requiring fewer patient clinical trials Currently, synthetic clinical trials tend to take the form of clinical trial sand arms as part of a large clinical trial program, i.e in the form of sub-project studies For example, extensive studies of blood pressure may benefit from sub-studies of different races This is a relatively simple classification of data But synthetic clinical trials are increasingly using data to tell you where the starting point is The industry can replace the method of carefully exploring the data on race by analyzing synthetic clinical trial data to identify patient queues that are the best treatments This data, often used in conjunction with other data sets, can point to new signals, including new indications For some light pipeline projects, the pharmaceutical industry's leading leaders ask: What other impact can therapeutic drugs have? once these signals are identified and endorsed the relevant pharmaceutical companies may be able to conduct very small controlled clinical trials instead of comprehensive clinical studies With the right data, innovators can be very close to results, even if they can't get results directly about two years ago, when the pharmaceutical industry first entered the field of research, synthetic data was used as a placebo-controlled arm The associated synthetic data, used to represent patients with standard therapeutic care, required the study to recruit only half of the patients normally used as test arms looking to the future, valuable data is key The NHS in England is seen as one of the key supports of the race Some of the world's largest pharmaceutical companies and technology entrepreneurs value the huge potential of data on the entire life span of the estimated 65 million patients covered by the NHS These can identify signals to new therapies, new therapies that help to detect diseases early, and basic information for patients best suited for clinical studies Companies such as Google, Bayer and Roche are all looking for new healthcare hopes and financial support as the NHS seeks new healthcare hopes and financial support The value of this data-sharing market is expected to soon reach $10 billion a year the rise of single-arm RWE trials the implementation of the 21st Century Cure Act, allowing more front-runners to develop evidence that no placebo-controlled evidence is in place With adaptive testing, the pharmaceutical industry is able to view data more frequently to determine when a product or administration does not work optimally, improving its ability to make changes to relevant participants Simply put, adaptive clinical trials allow teams to use predetermined rules to adjust and modify the trial process This approach can help researchers use fewer interventions in patients, save time, improve the relevance of trial results, and effectively reduce the resources needed to complete the study Until recently, almost all clinical trials followed the same sequence as shown in the following image: picture source: Resources, if the data meets the end point in the original design, it means good news, and the trial will be considered successful However, pre-design is often problematic: for example, in cases where the administration can be A, B or C, adaptive design enables innovators to introduce these assumptions and track results in real time When an option becomes a precursor, clinical trials tend to focus on confirming the results of a placebo-controlled trial picture source: Reference s2, reduce the intervention of clinical trial sites, is one of the main points of virtual trial But virtual clinical trials do not exist in the form of either, but in the form of a spectrum-like "you have me, I have you": there are completely virtual trials, and there is also a hybrid clinical trial approach picture source: Reference s2, in addition to traditional data analysis, some adaptive design, but also the use of centralized statistical analysis to identify possible patient internal errors, as well as patient-to-patient errors in both ways distorted data anomalies Most electronic data collection is correct, but if it goes wrong, it can have a significant impact on the speed and success of research The centralized monitoring team uses real-time data to identify and identify outliers through pattern sprees, marking errors, and getting rid of dependence on predefined data checks Statistical monitoring, visualization, and patient profiles help to identify previously undiscovered data quality issues 2020, how to deal with real-world research progress the new normal: to increase awareness of RWE
many companies are now only realising that the new normal is coming or is coming In this new normal, business success depends on support for RWE The industry must raise awareness of RWE and truly recognize that RWE is important for individuals and for the entire clinical development and commercialization process identify adaptive opportunities
in 2020, the industry will evaluate opportunities for applying adaptive considerations in their development plans The industry needs to strengthen the seamless design of Phase 2-3 clinical trials, new biomarker signals, and more complex medium-term analytical adjustment techniques through careful planning and in-depth epidemiological knowledge gained through RWD to try new designs
fewer clinical trials and one-arm designs for patients, using RWD to identify and identify external controls, can make trials more efficient, more valuable, and promising Expanding the use of RWD in a more creative way, supporting evidence generation and accelerating drug development, will be a priority for 2020 References: The BigSt Shifts Changing Lives and Life Sciences Dec 6, 2019 Retrieved Dec 7, 2019 from https:// 2 syneos Health® Insights Hub 2020 Health Trends Dec 6, 2019 Retrieved Dec 7, 2019 from https:// Syneos Health, Inc Syneos Health Insights Hub Releases 2020 Health Trends, Keying SShifts Trends And Commercialization Dec 9, 2019 Retrieved Dec 10, 2019 from https:// original title: Viewpoints - Real World Evidence Use Cases: What are the new developments and opportunities in 2020?