GenAI-OSCAR ML©/SCA
GenAI-Driven Synthetic Control Arm
Clinical Trials remain the most expensive, risky, ethically debatable and time-consuming aspect of drug development. Therefore, more improvement is needed in clinical trials.
Randomized controlled trials (RCTs) are the gold standard to investigate efficacy and safety of new treatments. In certain settings, however, randomizing patients to control may be difficult for ethical or feasibility reasons. If researchers are investigating a potentially life-saving treatment they believe will be particularly effective, it can be unethical to randomize the trial participants to a placebo arm.
Synthetic Control Arms (SACs) can be particularly useful in the rare disease and rare oncology spaces or even to increase an underrepresented subgroup of patients with a specific genetic or biomarker profile. Because these disease types have very small patient populations, it can be impractical or prohibitively difficult to find enough patients to enrol in an RCT, which can lead to sample sizes that are too small to obtain meaningful results.
In these circumstances, a SCA approach using RWD from EHRs can allow researchers to expand the sample size, ensure all study participants have access to the new medication, and accelerate the study timeline.
Why SCAs in Rare Diseases?
Overcoming Recruitment Challenges. Rare disease trials often struggle to recruit enough patients for traditional control groups. SCAs utilize real-world data (RWD) to create robust control arms, allowing more patients to receive the experimental treatment.
Ethical Trial Design. In rare and often severe diseases, it may be unethical to assign patients to placebo groups. SCAs provide an ethical alternative by using historical data as the comparator, reducing the need for placebo or less effective treatment arms.
Enhanced Study Feasibility. SCAs make trials feasible for diseases with extremely small patient populations by maximizing the use of available data, reducing the need for large control cohorts.
Accurate and Robust Data. By leveraging RWD, SCAs offer a reliable source of comparative data, enhancing the accuracy and robustness of rare disease studies.
Ideal Applications of SCAs in Rare Diseases
- Ultra-Rare Conditions: For diseases with extremely small patient populations, SCAs enable the execution of trials that would otherwise be unfeasible.
- Life-Threatening Disorders: In trials for severe or life-threatening rare diseases, SCAs provide an ethical alternative to placebo groups, ensuring that patients have access to potentially life-saving treatments.
- Precision Medicine: SCAs support the evaluation of precision or targeted therapies in rare diseases, where patient heterogeneity can make traditional control groups difficult to establish.
How GenAI-OSCAR ML©/SCA Enhances Rare Disease Trials?
- AI-Powered RWD Integration: aggregates and analyzes vast real-world data, including patient registries, medical records, and historical trials, to construct synthetic control arms that accurately reflect real-world patient populations.
- Advanced Data Modeling: the platform uses advanced machine learning algorithms to model disease progression and treatment outcomes, ensuring that the synthetic control arm is a precise match for the trial’s target population.
- Handling Missing Data: can generate synthetic data to replace missing or incomplete real-world data, providing a comprehensive dataset for robust analysis.
- Regulatory Compliance: SCAs developed using GenAI-OSCAR ML© are designed to align with regulatory standards, facilitating acceptance by authorities such as the FDA and EMA.
- Accelerated Trial Timelines: by reducing recruitment challenges and expediting data analysis.
- Cost-Effectiveness: lowers trial costs by reducing the need for large control groups and streamlining data processing.
- Enhanced Insights: provides robust and accurate comparative data, leading to more reliable study outcomes.
Why SCAs in Oncology Trials?
- Reduced Use of Placebos: in oncology, withholding treatment from patients through placebo control groups can raise ethical concerns, especially in life-threatening conditions. SCAs provide an ethical alternative by using real RWD as the control, ensuring all patients in the trial receive active treatments.
- Enhanced Recruitment: oncology trials, particularly for rare or aggressive cancers, often face difficulties in recruiting patients for control groups. SCAs help overcome this challenge by eliminating or reducing the need for large control cohorts, allowing researchers to focus on enrolling patients for the treatment arm.
- Accelerated Timelines: SCAs streamline the trial process, eliminating the need to recruit and monitor control patients in real time. This results in faster trial completion and a quicker path to regulatory approval, which is especially critical in oncology where timely access to new treatments can be lifesaving.
- Cost Efficiency: traditional control arms can be costly due to the need for larger patient groups and longer follow-up periods. SCAs leverage existing data, significantly reducing trial costs by minimizing recruitment efforts and administrative overhead.
- Accurate and Reliable Comparisons: SCAs built from RWD offer a detailed and realistic comparison that often reflects more diverse and real-world patient outcomes than traditional control arms. This can provide more robust data for assessing the efficacy and safety of novel cancer therapies, such as immunotherapies, targeted treatments or new radiotherapy schemes.
- Support for Rare and Advanced Cancers: SCAs are especially valuable in trials for rare or late-stage cancers, where patient populations are small and control groups are difficult to establish. By utilizing RWD, SCAs offer a feasible solution to study treatments in these challenging areas, ensuring scientific rigor even when traditional controls are impractical.
- Regulatory Acceptance: Regulatory authorities, including the FDA and EMA, are increasingly accepting externally controlled trials that use synthetic control arms. This growing acceptance ensures that oncology trials employing SCAs meet regulatory standards and can lead to faster approval of critical therapies.
Why SCAs in Neurology Trials?
- Enhanced Patient Safety: in cardiology, many conditions are life-threatening or chronic, making it ethically challenging to assign patients to placebo or non-treatment groups. SCAs provide an ethical solution by using RWD to create control arms, ensuring that all patients in the trial receive active or potentially beneficial treatments.
- Faster Recruitment: cardiology trials often require large patient populations and long follow-up periods, which can delay recruitment and slow down the trial process. SCAs, built from existing RWD, reduce the need for large control groups, allowing for faster recruitment and focusing on enrolling patients for the treatment arm.
- Accelerated Time to Market: with SCAs, cardiology trials can bypass the lengthy process of building traditional control groups from scratch. By utilizing RWD, SCAs provide a quicker path to trial completion, leading to faster regulatory submission and approval, which is critical for life-saving cardiovascular therapies.
- Cost Efficiency: traditional control arms in cardiology can be expensive due to the need for long-term patient monitoring and large-scale recruitment. SCAs, which leverage data from previous trials, medical records, and real-world outcomes, reduce the need for these costly control arms, leading to significant cost savings in trial execution.
- Accurate Representation of Real-World Patients: SCAs use RWD to more accurately reflect the diversity and complexity of cardiovascular patients seen in everyday clinical settings. This ensures that trial results are more representative of the broader patient population, enhancing the generalizability of the findings.
- Addressing Rare and Severe Cardiovascular Conditions: for rare cardiovascular conditions or severe cases where traditional randomized controlled trials (RCTs) may not be feasible, SCAs offer a solution by utilizing existing data as the control. This makes it possible to evaluate treatments for conditions where it’s difficult to recruit large control cohorts.
- Support for Device and Intervention Studies: in cardiology, many trials evaluate new devices or interventions, which may be challenging to study using traditional RCTs. SCAs allow for efficient comparison of these treatments without the need for extensive control groups, speeding up the evaluation process while maintaining rigorous standards.
- Regulatory Acceptance: regulatory bodies like the FDA and EMA are increasingly accepting externally controlled trials, including those using SCAs, especially in cases where traditional control arms are impractical. This growing acceptance ensures that cardiology trials using SCAs meet regulatory requirements and can lead to faster approval processes.
Why SCAs in Cardiology Trials?
- Addressing Recruitment Challenges: neurological disorders often involve small or heterogeneous patient populations, making it difficult to recruit adequate participants for traditional control groups. SCAs, built from RWD, eliminate or reduce the need for large control arms, making trials more feasible and speeding up patient recruitment.
- Ethical Considerations: many neurological conditions, such as ALS, Alzheimer’s disease, and advanced Parkinson’s disease, are progressive and debilitating, making it ethically challenging to use placebo controls. SCAs offer an ethical alternative by using historical or RWD, allowing all patients to receive active or investigational treatments.
- Faster Trial Completion: neurological trials often require long follow-up periods to observe meaningful changes in disease progression, which can significantly extend the trial timeline. SCAs streamline this process by using existing data for the control arm, reducing the time required to conduct the study and enabling faster regulatory submissions.
- Capturing Disease Complexity: neurological disorders are often highly complex, with significant variability in disease progression and patient responses. SCAs utilize RWD from diverse populations, allowing for more accurate modelling of the disease’s natural course and improving the reliability of the comparisons between treatment groups and control arms.
- Cost Efficiency: conducting traditional control arms in neurology trials can be expensive due to the need for large-scale patient monitoring and extensive follow-up. SCAs significantly reduce trial costs by using RWD as the control, eliminating the need for large and costly control cohorts while still providing robust comparative data.
- Rare Neurological Conditions: for rare diseases such as Huntington’s disease or rare forms of epilepsy, where patient populations are very small, SCAs offer a practical solution. By leveraging data from existing registries, previous trials, or medical records, SCAs make it possible to conduct clinical trials that would otherwise be unfeasible due to recruitment limitations.
- Improved Regulatory Acceptance: regulatory bodies, including the FDA and EMA, are increasingly open to externally controlled trials that use synthetic control arms, especially in cases where traditional RCTs are difficult or unethical. This growing acceptance of SCAs ensures that neurology trials using this approach meet regulatory standards, potentially expediting the approval process.
- Evaluation of Novel Therapies: neurology is at the forefront of cutting-edge treatments, such as gene therapies, cell therapies, and precision medicine approaches. SCAs provide a reliable way to assess these novel therapies by offering a robust and ethical comparison group, even when traditional controls are not feasible.
All Our Services
GenAI-Driven Synthetic Control Arm
GenAI-Driven RWD Acquisition & Analysis
Target Trial Emulation for Drug Repurposing
Realistic and Privacy-guarantees Synthetic Patient Data
Clinical Trial Simulation in Silico
Patient’s Data De-Identifier
GenAI-Driven Remote Verbal Consent
CONTACT DETAILS
info@aimedtrial.com
+39 3482630229