Oncology outcomes and regulatory studies need highly detailed, representative and regulatory-grade patient data to answer important clinical questions – at scale and with confidence.
Concerto HealthAI’s next-generation outcomes science research model takes a unique, data science-centric approach.We engineer Real-World Data products and work with health economists, clinical and regulatory experts and data scientists with a keen understanding of data and AI technology to deliver regulatory-quality studies that are innovative, faster and lower cost.
Conduct vastly superior safety, efficacy and comparative effectiveness research with oncology RWD that is the largest in the industry and has the deepest unstructured abstraction specifications in the market.
We take a strategic approach to each Outcomes Science project, helping Clinical Development and Medical/HEOR organizations conduct retrospective studies that get to the core of patient experience more quickly and efficiently. Our expansive oncology RWD gets to target demographics and clinical characteristics, treatment patterns through multiple lines of therapy, effectiveness outcomes (PFS, OS, Best Overall Response, etc.), health resource utilization and cost of care models at a fraction of the time and cost of traditional methods. Our team of HEOR scientists, research nurses, analysts, statisticians, and medical writers bring deep domain expertise to synthesize data and compare it across treatment groups or subgroups based on clinical characteristics.
Publication planning drives study design and considers all stakeholders, including clinical, regulatory, reimbursement and business needs. And, as payers and regulatory authorities increasingly demand Patient reported outcomes (PRO) as integral evidence of value, our deep oncology expertise and datasets lets us design PRO studies that more effectively connect the dots between adherence and quality of life.
Synthetic Control Arms
The increasing costs of clinical trials, extreme challenges of cancer patient enrollment, rising patient concerns around placebo groups and need for strong confirmatory evidence of value in medical affairs and value dossiers have made Synthetic Control Arms (SCA) a welcome and critical aspect of regulatory submissions and risk mitigation during the drug development process.
When the primary focus is regulatory filing, SCAs facilitate faster, more efficient and cost-effective research. They can benchmark summary data as test values against single arm trials or conduct two-arm studies with or without patient matching. SCAs can also be leveraged for confirmatory studies on patients receiving a specific treatment (single-arm) or to compare patients receiving a drug with those who are not (two-arm). Concerto HealthAI’s solutions have shown reductions of 50-75% in the cost of regulatory RWE studies.
During the drug development process, effectively designed SCAs can significantly accelerate insights and analytics needed to make go/no-go decisions on therapies earlier in the process – reducing costs and, ultimately, improving patient outcomes by bringing much-needed treatments to market faster.
Hybrid Retrospective Studies
How do you address the increasing regulatory and reimbursement burden of demonstrating Real-World Evidence of value after your drug hits the market, especially when its more challenging than ever to find and enroll cancer patients into prospective trials?
Concerto HealthAI’s industry-leading and rapidly growing clinical oncology dataset with access to six different EMR systems and over 1.5 million unique patients is helping biopharma clients address these RWE challenges.
Our Hybrid Retrospective studies replace traditional Phase IV prospective studies with cost savings of up to $10M. Deeply abstracted and continually refreshed datasets of historical patient cohorts, with accrual of patients most recently treated and under active treatment, let you answer a variety of questions, including how they were treated, occurrence of adverse events, tumor response and PFS and OS rates.
We combine deep domain expertise with powerful technology. AI methodologies like machine learning and pattern recognition, and experienced oncology nurses and Natural Language Processing (NLP) capabilities drive the deepest data abstraction and quality assurance standards in the industry. And our HEOR scientists provide strategic input to CRF development, ensuring that publication planning and key data points are captured.
Outcome Science Services
Our Functional Service Provider (FSP) status lets us bring the right resources to you at the right time. We have outcomes science experts who understand the clinical and regulatory environment working alongside data scientists who are applying advanced technologies like Natural Language Processing (NLP) and Artificial Intelligence, such as deep learning, supervised learning and pattern recognition for deeper data exploration, discovery and analysis – to design and deliver next-generation outcomes research studies.