Real World Data Evidence Services
Empowering pharmaceutical and life sciences enterprises with platform-driven advanced analytics approach to real world evidence
Need for Real-World in Healthcare
Expanding ecosystem of health-related data has led to opening of greater opportunities for the healthcare industry to get the right treatment to the right patient. There is growing emphasis on generating and using Real World Data (RWD) to evaluate continued safety and effectiveness of products.
Key Challenges
- Conceptualizing an engaging RWE strategy integrating multiple stakeholder interests
- Availability of the right cross-functional skill-sets for effective solutions implementation
- Solutions with consistent standards for data management and interpretation
- Systems that ensure inter-operability and compatibility across datasets
- Compliance with regulatory and ethical requirements such as data privacy and data security
- Managing the ever-increasing volume of complex data
How Do We Help?
01
Highlighting product differentiation that adds depth to product value proposition at launch and beyond
02
Enabling seamless translation of efficacy to effectiveness and reduce evidence uncertainty
03
Easily identifying patient subgroups that will benefit most from an intervention
04
Understanding unmet patient needs to guide and optimize drug development programs
05
Generating value-based evidence to characterize drug efficacy and healthcare resource utilization to support payer coverage and patient reimbursements
Actu-Real RWE Service Offerings
Defining RWE Strategy
Integrate stakeholder requirements
and define an RWE strategy that
meets the needs of –
- Clinical development programs
- Target Product Profile
- Commercialization plans across geographies
- Comparative Effectiveness
Generation of RWD
Conduct and execution of observational studies of such as –
- Retrospective and prospective
- Patient registries, chart reviews, surveys, disease background reviews
- Burden of illness studies
- Studies to help devise strategies to improve adherence, and establish safety profile
RWD Analytics & Evidence Synthesis
PLEASE SHARE CONTENT FOR THIS BLOCK
- Systematic reviews
- Meta-analyses, network meta-analyses
- Indirect treatment comparisons, propensity score matching
- Predictive modeling
- Longitudinal clinical and claims data analysis
The Actu-Real Advantage
Pragmatic and fit-for-purpose solutions combined with cross-functional expertise across clinical development, real world evidence, health economics, data sciences and actuarial science
Premium clinical trial support along with best-in-class statistical expertise for efficient clinical trial design
HERCULE™ - a modular platform with pre-configured statistical models that can be readily deployed to ingest, analyze and visualize real world data
In-depth experience that spans across the pre-launch and post-launch continuum
Innovative solutions in areas of value-based healthcare and risk-sharing agreements that help manufacturers and payers understand market performance before launch
An all-encompassing solution that covers both platform and services using a highly efficient global delivery model
FAQs
FDA defines RWE as the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of real-world data (RWD). RWD are the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources.
RWD come from various sources like electronic health records (EHRs), claims and billing activities, product and disease registries, patient-generated data including in-home-use settings, and from other sources that can inform on health status, such as mobile devices.
While clinical trial data provides the basis for drug approval, it doesn’t cover all aspects from the real world due to its homogenous patient groups defined by inclusion/exclusion criteria and its fixed setting as per the study protocol. RWE helps bridge the gap between research and everyday practice in healthcare. It serves the following uses:
- Helps manufacturers and regulatory authorities monitor post-marketing safety and adverse events and to make regulatory decisions.
- The healthcare community is using these data to support coverage decisions and to develop guidelines and decision support tools for use in clinical practice.
- Medical product developers are using evidence generated from observational studies to develop new treatment approaches and identify patient subgroups that will benefit more from the product.
- RWD is also used to design clinical trials, in aspects such as defining eligibility criteria and identifying patients for recruitment. RWD is being increasingly used to create synthetic control arms (SCA) when controlled clinical trials are not feasible.
Replicability is the ability to confirm findings in different data and populations. There are several ongoing efforts that aim to replicate the results of RCTs using rigorously designed and analyzed observational studies, including by the FDA. The most prominent such effort (RCT DUPLICATE) is a collaboration between FDA, Brigham and Women’s Hospital and Harvard Medical School Division of Pharmacoepidemiology. This initiative aims to replicate 30 completed Phase III/IV trials using Medicare and commercial claims data, and to predict the results of seven ongoing Phase IV trials.
An EMR is a digital copy of a patient’s paper records – contains patient’s medical data, history, and the treatments given by a particular provider, hence a digital version of a record from a single provider.
An EHR is a digital record of health information. It contains all the information from a paper record plus additional details like immunization dates, allergies, lab data and imaging reports, insurance information, demographic data, data imported from personal wellness devices, etc. Essentially it is the complete digital record of the health information for a person.
EMR is not designed to be shared outside the individual practice and is mainly used by providers for diagnosis and treatment. On the other hand, EHR allows patient data to move with them and can be shared between providers, labs, etc and can be used as a tool by providers to make decisions since it holds real time information.
Comparative effectiveness research (CER) as defined by the Institute of Medicine, USA is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care. The purpose of CER is to assist consumers, clinicians, purchasers, and policymakers to make informed decisions that will improve health care at both the individual and population levels. It involves comparison of two or more agents, medical devices, procedures, health services, or any other competing interventions that are considered true therapeutic alternatives in actual clinical practice.
In clinical trials, real-world data may be collected from patients as patient-reported outcomes (PROs), in the form of questionnaires or surveys. Patient-generated data from home-use settings or through other sources like mobile devices etc also qualifies as real-world data that may be captured in a clinical trial.
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