NLP-Aided Systematic Literature Review (SLR).
Cut Through Mountains of Scientific Literature in Seconds with CapeStart’s Text Mining Software and Processes.
SLRs play a critical role in health-care decision-making, but also take an incredible amount of time and effort to produce. The machine learning and natural language processing experts at CapeStart can semi-automate the SLR process flow – reducing time spent, improving accuracy, and scaling your team’s effectiveness.
Produce Full-Throttle SLRs in Half the Time.
Health-care decision-makers rely on SLRs for the best treatment option out of multiple potential therapeutic interventions. But SLR creation involves numerous high-intensity and time-consuming tasks – including question formulation, inclusion criteria, and scientific literature text mining – which can take months to complete, leaving some SLRs hopelessly out of date by the time they’re published.
That’s why CapeStart’s semi-automated, human-in-the-loop ML and NLP approaches for SLRs provide the utmost speed without sacrificing comprehensiveness, rigor, or accuracy.
- How social media is an early indicator of upcoming serious ADRs.
- Blending human effort with AI technology to solve this problem.
- Our quality and ability to involve experts such as MDs for case reviews
- Team well-versed in media monitoring and pharmacovigilance.
- Flexibility to present reports in various formats.
NLP-Aided Solutions for SLRs and Meta Analyses.
CapeStart’s proprietary, NLP-aided solution semi-automates the generation of SLRs and meta analyses by combining
- An all-inclusive search engine for evidence search
- An intuitive workflow tool enabling real-time collaboration and customized reporting
- An NLP engine to aid all decision-making, from title & abstract review, to inclusion criteria, to data extraction
- An automated meta-analysis platform that generates forest plots/blobbograms and other statistical representations
- An automated alerting system that notifies the user/team of new and relevant research updates
- A fully automated, NLP-based evidence mapping system that’s constantly learning from the review team and visualizing the spectrum of evidence
What We Deliver.
AI and Development Services for SLR and Meta Analyses.
CapeStart's team of data scientists and NLP experts customize AI models that enhance the generation of SLRs by research organizations
We can deploy a combination of customized and pre-built ML/NLP models to:
- Quickly identify and extract relevant studies across tens of thousands of sources
- Improve PICO identification for the formulation of clinical research questions
- Improve extraction of required data elements from full-text sources
- Intelligently map evidence gaps to drive future research
Consulting and Data Services in Health Economics and Outcomes Research (HEOR).
CapeStart’s expert biostatisticians and experienced subject matter experts perform SLRs and meta analyses for the world’s leading biopharma, medical device and public health innovators
Contract research services include:
- Understanding the significance and scope of clinical research questions for SLRs
- Identifying, extracting, and compiling the most relevant and accurate real-world evidence from peer-reviewed studies and other sources
- Extracted data synthesization and meta analysis generation in compliance with established international methodologies
- Regular SLR and meta analysis updates based on new studies and information
What’s the CapeStart Difference?
We’re SLR Experts
CapeStart’s biostatisticians, healthcare data analysts, cardiologists, oncologists, and other SMEs have years of experience producing cost-effective and accurate SLRs for leading life sciences companies.
We’re NLP in Life Sciences Experts
Lean on our extensive experience labeling and annotating complex medical reports, radiology images, diagnostics, clinical trial data, real-world evidence, and pharmacovigilance data.
We Meet Every Deadline
We’ll tackle any project, any data type, and any data volume – no matter how complex or unwieldy – and turn it into actionable intelligence, even on a tight turnaround.
We’re Cost Optimized
CapeStart’s integrated, in-house team uses field-tested methodologies and processes proven to optimize costs and deliver the most relevant, accurate results possible.
Systematic Literature Review Use Cases.
CapeStart helps research organizations across the healthcare spectrum produce literature reviews faster, more efficiently, and more accurately through the power of AI.
Medical device manufacturers must evaluate their medical devices before entering the market. These evaluations include technical specifications, instructions for use, a risk assessment, evidence on biological safety, and a clinical evaluation. A clinical evaluation report analyzes clinical data concerning the safety and efficacy of the medical device and equivalent or similar devices. This risk-benefit analysis is a process very similar to preparing a systematic literature review.
For these use cases, Capestart’s NLP-based solution runs a precise literature search that saves time and effort when collecting evidence.
Scientific literature monitoring for adverse events is an important aspect of pharmacovigilance. Although the current process is very systematic, recent exponential growth in the volume of medical literature presents a unique opportunity to improve traditional processes of manual screening, reviewing, and monitoring through technology.
CapeStart has developed AI models that effortlessly integrate data from multiple information sources to identify adverse events faster and more accurately than previously possible, saving considerable time and effort when conducting large scale analyses.
Rising drug discovery costs and an increasing focus on rare diseases have spurred scientists to find new uses for existing drugs through drug repurposing. Drug repurposing takes advantage of already-approved drugs with well-known safety and pharmacokinetic profiles, and that have already been through clinical trials.
Capestart’s NLP-based solution helps discover potential new applications of existing drugs by extensive, systematic literature analysis, including combing through existing drug-disease knowledge to identify disease–gene, gene-drug, and disease-drug relationships.
Drug discovery and development often begins with the identification of a new drug target – a crucial step before embarking on the time-consuming, expensive, and high-risk drug development process. Literature research plays a vital role in identifying new drug targets, including understanding target biology and links between targets and disease states.
Capestart’s NLP-based solution goes further than simple lexical recognition to interpret full-text documents by understanding syntax and semantics – combined with other layers of analysis – to help with early target identification, which can be a considerable business advantage.
Precision medicine (or personalized medicine) is a promising approach to tackling previously untreatable diseases. This emerging approach for disease treatment and prevention takes into account individual variability in genes, environment, and lifestyle. Scientific literature provides a wealth of data on the impact of genetic variability on disease states and drug responses – but finding the right articles from the ever-growing scientific literature is a huge challenge.
Capestart’s NLP-based solution provides an alternative to traditional search methods by identifying causal genes and rapid extraction of actionable insights from multiple data sources, to produce more consistent and accurate information.