Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the pharma industry. This time, you get to discover five hand-picked real world evidence startups.
Out of 110, the Global Startup Heat Map highlights 5 Top Real World Evidence Startups
The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.
The Global Startup Heat Map below reveals the distribution of the 110 exemplary startups & scaleups we analyzed for this research. Further, it highlights five pharma startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these five startups & scaleups in this report. For insights on the other 105 real world evidence solutions, get in touch with us.
Pentavere provides Unstructured Health Data Analytics
Real-world evidence is clinical evidence derived from a range of interventions that a conventional randomized controlled trial (RCT) does not record and is grouped under real-world data (RWD). It mainly comprises unstructured health data from a wide variety of sources. These include patient registries, electronic health records (EHRs), pharmacy and insurance databases, wearables, and patient-powered research networks (PPRN). Pharma companies now collect and analyze RWE to improve their solutions.
Pentavere is a Canadian startup that provides lifesaving insights from unstructured health data. Its proprietary engine, DARWEN, uses artificial intelligence (AI) and natural language processing (NLP) to extract complex information from text data. This includes unstructured documents such as clinical notes, transcription text, lab tests, as well as imaging and pathology reports.
Concerto Health AI advances Regulatory Research
Regulatory research in the pharmaceutical industry ensures that the products meet the required standards of safety and efficacy. RWE offers new metrics to measure and improve the methodology and reliability of data in clinical trials. Therefore, including sources of RWE boosts the prospects of pharma companies to receive regulatory approval for clinical trials. The US Food and Drug Administration (FDA) has even issued guidelines on best practices to report pharmacoepidemiologic safety using EHRs.
The US-based startup Concerto Health AI offers integrated real-world evidence solutions. It explores research-grade RWD to simulate and compare patient population size and characteristics. This allows companies to quickly find patients who benefit, and are underserved, by current therapeutic approaches. The solution enables robust, high-confidence clinical study designs and external control arms.
AKESO offers a Real Clinical Practice Data Plaform
Even a clinically-proven drug often shows varied effects in different patients. Other than genetics, these differences usually result from differences in co-morbidities, treatment patterns, or adherence. RWE from electronic health records allows pharma companies to understand these variations and test the efficacy of their drugs in use.
AKESO is a Russian startup that provides RWE reports to pharmaceutical companies. It receives data directly from inventory information approval systems (IIAS) of hospitals and clinics. The solution uses AI and machine learning to analyze depersonalized EHRs to identify patient profiles and predict key performance indicators (KPI) for preferred therapies. It also enables mathematical modeling of drug efficacy across different patient subgroups.
Embleema enables Preclinical Target Discovery
RWE also finds applications in drug target discovery. RWE-based solutions integrate and analyze genomic sequencing data and clinical data from a cohort of patients. It allows pharmaceutical companies to identify biomarker targets of interest. It also offers valuable insights from multi-omics data to guide the development of precise therapies.
The US-based startup Embleema leverages RWE for preclinical target discovery. It integrates omics data, such as genomics, metabolomics, proteomics, and glycomics, from patients with electronic medical records, patient reported outcomes, and data from connected devices. The solution allows pharma companies to analyze this data to discover pre-clinical targets and speed up approvals for precision medicine drugs.
PatchAi develops Software as a Medical Device (SaMD)
Continued patient management is a challenging task during clinical trials. Analysis of RWE from patients in clinical trials helps researchers understand the factors that contribute to patient drop-outs. Moreover, it also helps accelerate and improve the recruitment process for clinical trials, particularly for rare diseases.
PatchAi is an Italian startup that develops an AI-powered digital health solution for patient engagement and data collection. The SaMD platform is a virtual assistant that helps patients play an active role in generating RWE. It focuses on personalized patient experience and engagement to facilitate electronic patient reported outcomes (ePRO). The solution is configurable for individual study protocols and to optimize clinical trial workflow and timelines.
Discover more Pharma Startups
Pharma startups such as the examples highlighted in this report focus on improving the utilization of electronic health records, the process of clinical trials evaluation, and target discovery. While all of these technologies play a major role in advancing the pharma industry, they only represent the tip of the iceberg. To explore pharma technologies in more detail, simply let us look into your areas of interest. For a more general overview, download our free Pharma Innovation Report to save your time and improve strategic decision-making.
