SAS Real World Evidence

The data collected during treatment have huge potential. They help the industry to develop and conduct clinical trials, to estimate use of medical services in the different countries and to identify patients from risk group. SAS Real World Evidence offers the organizations tools for collecting and obtaining information from such data.

The product gives opportunities of analytics, visualization, artificial intelligence and machine learning to the organizations which work with constantly increasing number of data on health.

2020: Integration of a packet of Wolters Kluwer Health Language into SAS Real World Evidence

On March 16, 2020 the SAS company announced the conclusion of the partnership agreement with company Wolters Kluwer, Health, the supplier of professional information, software solutions and services for health care. The companies began joint work over quality improvement of medical data: the solution package of Wolters Kluwer Health Language is integrated into the SAS Health portfolio. This step will help to unify information collected from a set of separate sources using the advanced analytical solution SAS Real World Evidence and also to put basic standards of quality of medical data of real clinical practice.

According to the research Research and Markets, it is expected that by 2024 the market of data of real clinical practice (Real World Evidence, RWE) will reach the level of 1.64 billion dollars USA. It is connected with its potential – there is more and more understanding what effect these or those methods of treatment give, diagnostics is specified, there are more data on mechanisms and weight of diseases and also clinical trials accelerate and optimized. These data come from the most different sources – medical records, registers of diseases, next-to-skin electronic devices, arrays of the genetic given, medical account, etc. In similar conditions purity of data of RWE is extremely important: the uniform quality standards of data in all industry are necessary for their successful analysis.

The pharmaceutical companies and regulators are interested in obtaining deeper data on real use of medical products and medicines which serve as the valuable addition to the data collected at a development stage. The main objective is in better to study therapeutic effect of application of a medical product (devices, drugs or vaccines) patients in the conditions of real clinical the practician who often differs from estimates of patients from randomized clinical trials. The solution SAS Real World Evidence thanks to the scalable analytical platform gives to researchers of medical data a convenient and reliable working environment. At their order – tools for data management, Hadoop integration, the accessibility for any user and also visualization and data analysis of cohorts. Quick access to the valuable data taken from data of real clinical practice, in turn, gives competitive advantage in questions of development and marketing and allows to make proved the decision on an output of new products to the market.

Pharmaceutical industry stakes on use of data of real clinical practice for building of strategy in the present and in the future. However there are data sources, and heterogeneity of this information becomes an obstacle in a way to implementation of these initiatives. SAS in partnership with Wolters Kluwer, Health creates a full-fledged ecosystem of qualitative data which will provide to our clients competitive advantage, – Alexander Zhukov, the Head of Department of solutions for health care of SAS Russia/CIS speaks

2018: Sharing of cohorts, projects and data

On November 19, 2018 the SAS company presented solutions of the next generation for data analysis of clinical trials: SAS Real World Evidence and SAS Life Science Analytics Framework. The updated solutions estimate medicines better, investigate data on patients and efficiency of treatment and will help to provide quicker to the market safe methods of treatment, declared in SAS.

Among opportunities of SAS Real World Evidence in the company noted the following:

• Optimization of the requests given for accomplishment — reduces time for creation of cohorts and accelerates process of the analysis.
• The possibility of sharing of cohorts, projects and data — promotes more dense cooperation between the users programming on SAS, and those who prefer not to program.
• An opportunity to use the checked algorithms for the analysis or to add own macro libraries for expansion of data access, to analyses and analytical data on all organization.