"Wan Aike (commonly known as Viagra) is a new drug for heart disease invented by scientists. It is hoped that it can treat angina pectoris, but in the course of clinical trials, through the clinical response data submitted by a large number of patients, it was found that the drug actually turned to ED ( Sexual erectile dysfunction patients have obvious curative effects. Scientists have changed their slogan and increased their research investment in this area. Only then has the world-famous 'Viagra', which is an ancient feature of the early real world research. One of the cases." Kang Zhiqing, vice president of AstraZeneca Medical, said at the 2018 Medical Affairs Leaders Summit held recently.
"RWE" complement "RCT"
What is "real world research"? Real-world research (RWE) originated from practical clinical trials and was first used in the field of drug epidemiology, specifically on the basis of a large data sample size (covering a representative and broader population of subjects). In the medical process, non-randomized treatment measures are based on the patient's actual condition and willingness, long-term evaluation is carried out, and meaningful outcome treatment is emphasized, and the external validity and safety of the intervention are evaluated in a wide range of real medical procedures.
However, the emergence of randomized controlled trials (RCTs) is much earlier than real-world research, so it has been used as a "gold standard" for drug clinical trials in the industry, but its limitations have become more prominent.
It is understood that in the era of evidence-based medicine, RCT-based research methods have indeed solved the effectiveness and safety of new drugs, but it has also brought many problems and problems. In fact, RCT has selected a certain number of selected exclusion criteria. The specific population of the sample leads to more restrictions in the inclusion of the population, and the strict control of the medication conditions makes the internal authenticity of the research results higher, but the external authenticity is poor, and the scalability in real clinical practice cannot be determined. In addition, due to the design of control variables, RCT rarely obtains information about concomitant diseases and concomitant treatments, and in order to comply with research protocols, more interventions are often taken, which is not realistic in clinical practice. In general, RCT has “three highs and three smallsâ€: high selection of people, high cost, high internal consistency, short study time, small sample size, and small representation in the real world. Therefore, many scenarios in clinical research Not suitable for RCT.
It is precisely because of the above-mentioned problems in the RCT that the above-mentioned promotion in clinical practice is limited, so that there is a "one place to use" in real world research. "Real world data can solve problems that RCT cannot solve in the past. In recent years, real World research is beginning to receive increasing attention and attention from the medical community. For example, the FDA issued the “Decision on the Use of Real-World Evidence to Support Medical Device Regulations†in 2017, which defines FDA's use of real-world evidence for medical devices. The attitude of the review," said Gu Chengming, vice president of Pfizer Medicine.
In China, special standards for real-world research are also entering the industry's vision. On August 3 this year, Wu Yilong, the chairman of the Department of Oncology and Medicine of Wu Jieping Medical Foundation, led the official publication of the “Real World Research Guide†written by relevant experts, which will help Chinese researchers to better carry out RWS research. On September 6th, the "Real World Research Practice Expert Consensus" written by Zero Technology participated in the release. The "Consensus" talks about basic issues such as the status of RWS at home and abroad, and explores the existing misunderstandings, processes, and application scenarios of RWS. It is hoped that through the implementation of RWS, the massive medical data obtained under real-world conditions in China will form real-world evidence, so that high-quality real-world evidence will become the best clinical evidence, solve the current situation of insufficient clinical evidence in China, and enhance the international academic status.
“From start to finish†runs through the entire lifeline of new drug development
“It can be said that real-world research runs through all stages of new drug research and development, drug marketing and post-marketing.†Li Liping, co-founder and chief clinical operations officer of Zero Technology, told Medical Valley, “In the laboratory stage of drug development, the real world Research can help discover new targets for drugs; in the clinical phase, real-world research at this stage can understand the burden of disease and unmet needs in drug-related therapeutic areas, allowing for market prospects, such as learning from real-world databases. The disease has existing treatment products, treatment information and other information. At the same time, it can accurately find the hospitals and departments where the target patients are distributed, helping to recruit patients who meet the inclusion criteria more quickly; in the drug application application stage and review stage, Real-world research can help identify drug safety risks, such as risk management plans, pharmacovigilance programs, risk management minimization programs, etc. Once a drug is approved for marketing, the regulator will continue to monitor real-world patient use to continue Judging the risk-benefit situation of drugs, at this stage, Collecting patient use on a large scale, conducting safety and effectiveness monitoring in real-world research, managing lifecycle products, and using real-world data to conduct health economics evaluations."
It is precisely the importance of real-world research in drug research and development. Zero-æ°ª technology is working on the corresponding force layout. According to Li Liping, Zero-Tech is a medical big data company, which has a blessing of massive quality medical data. The company has reached a number of strategic cooperation with pharmaceutical companies and hospitals to help them recruit patients. In order to be more professional, Zero Technology invested in the acquisition of one of the early recruiting companies in the industry--Beijing Houpu Medical Technology Co., Ltd., "According to real-world data, it can accelerate recruitment and recruit patients more accurately. As of the first half of this year, we have completed the recruitment index equivalent to last year, and we expect to achieve twice the target of last year by the end of the year. To benefit more patients."
All in all, real-world research has strong external representations, interventions that are consistent with clinical practice, clinical practice environment, no blinding, no placebo, and can be uncontrolled and reflect the effects of “patients†(disease management). Not only the efficacy of “diseases†but also the characteristics of health promotion and health decision-making can be directly derived from clinical practice. Real-world research can not only reduce the limitations of traditional research, but also reflect the clinical efficacy of therapeutic drugs in the real world, provide an objective basis for clinical selection of new drugs and new devices, and balance clinical efficacy and cost-effectiveness with real-world data evidence. At the same time, it will also speed up the approval of the listing of drugs.
It is foreseeable that the impact of real-world research on the pharmaceutical industry will range from what was once “dispensable†to “indispensableâ€.
Data standardization is low, how to break
Although real-world research has so many advantages, it also faces many challenges: for example, real-world research requires a large amount of research data samples, and the medical clinical big data collected in China has not been uniformly standardized, and heterogeneous is serious. In other words, the volume of medical data is large but the degree of standardization is very low. In addition, the HIS system of China's medical service institutions is a battalion, and there is no national disease database. All of these have become the development constraints of real world research.
Yang Haiying, the chief medical officer of Zero Technology, also expressed the same concern. She said: "The lack of standardization and standardization of medical clinical big data has two major factors: one is the data source itself, and the other is data processing capability. The data source itself, in fact, its writing quality requirements for hospital cases is very high, if you want to improve the standardization and standardization of medical records from the source, the quality and specification of the original case is essential. For the data processing ability, in fact, many There is no clear concept of data processing for real world research. The whole process of data processing includes important steps such as input, data coding normalization and quality control. First of all, data entry is not completely solved by machine learning. From the perspective of the entire entry, it is also based on the progress of computer research and learning can effectively deal with certain types of data, but a considerable part of the text content still needs professionally trained labor, so at this stage the combination of machine and labor Data processing method for data entry processing Secondly, the recorded information in the medical records is required to be professionally coded and normalized using an internationally recognized coding dictionary, which is the basis for subsequent statistical analysis; again, the entire process of data processing Quality control requirements are quite high, and a complete quality control system is required to ensure the accuracy of data processing. At the same time, it is very important to verify the accuracy of data by professionals with medical background. However, due to the special nature of the hospital, There is no professional technical team to process data internally, which brings opportunities for big data companies like Zero Technology."
According to Medical Valley, in order to standardize and structure the hospital's data, Zero-Tech has established a set of intelligent data processing system, which can centralize the processing and verification of clinical data, in the process of processing the entire data. There are advanced machine learning technology applications to improve efficiency, and very professional medical personnel to participate in the whole process of planning and verification, thus carrying out a "double guarantee" in quality and efficiency.
It is also known that as of the first half of 2018, Zero-Tech has accumulated nearly 3 million structured medical records, and this data is still gradually expanding. On this basis, Zero-Tech is currently promoting real-world research. Massive real data is used in many scenarios such as artificial intelligence research, clinical research, drug development and evaluation, and medical insurance payment.
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