Hybrid Quantum-AI Solution for Clinical Trial Optimization: Driving Impactful Advances in Healthcare

Bringing new, life-saving, and life-changing therapeutics to market requires an average of 10–15 years and an investment of USD 1.5–2.0 billion, with extended clinical trials playing a crucial role in the process. The complexities of patient and cohort selection, clinical trial design, and regulatory compliance present significant challenges. Additionally, trials require companies to balance multiple factors, including patient cohort sizes, trial locations, safe and effective dosages, and study durations, while minimizing biases and optimizing both statistical power and costs. These elements collectively contribute to the extensive challenges faced during clinical trial operations.

Each clinical trial design has its own specific set of optimization challenges impacting efficacy, safety, and cost-effectiveness. Distinct objectives in each phase (Phase I: Safety, Phase II: Efficacy, Phase III: Confirmation) must adhere to strict protocols, regulations, and procedures. This multi-variable optimization, along with newer methods such as adaptive trials, makes optimal human clinical trial designs challenging and extraordinarily time-consuming to achieve.

Clinical Trial Phases

Clinical trials typically involve four phases:

• Phase I: A small group of healthy volunteers test the drug's safety and determine the appropriate dosage.
• Phase II: The drug's efficacy (effectiveness) is evaluated in a larger group of patients with the target condition.
• Phase III: Confirmation of efficacy and safety happens in a much larger and diverse patient population.
• Phase IV: Long-term safety and effectiveness are monitored after the drug is commercially available.

Financial Burden

The extremely high cost of human clinical trials impacts everyone involved:

• Patients’ Survivability: Delayed access to potentially life-saving treatments due to slow clinical trial progress is a life-or-death race against the clock.
• Pharmaceutical and Biotech Companies: The R&D costs associated with lengthy trials significantly impact profit margins.
• U.S. Government costs: In 2022 alone, the U.S. Government spent $4.5 trillion or $13,493 per capita. Overall, health spending was 17.3% of GDP in 2022. There is huge taxpayer interest worldwide in bringing down the overall costs of healthcare delivery.
• Market Competition: High costs also ensure that only the best-funded companies can bring a safe, effective drug to the market.
• Healthcare Industry: Rising drug development costs translate to higher healthcare costs in the U.S. as costs are passed on to patients, government-funded subsidies such as Medicare and Medicaid, and the insurance system – all of whom currently bear the lion’s share of costs.

Here at Artificial Brain , we're revolutionizing this process with our innovative Hybrid Quantum-AI solution. This powerful solution leverages the combined strengths of Quantum Computing and Artificial Intelligence (AI) to optimize clinical trial design.

Unveiling the Power of Hybrid Quantum + AI Solution

AI excels in handling large datasets to uncover patterns and make predictions based on existing information, which is pivotal in the early phases of clinical trials for tasks such as patient selection and predictive outcomes based on historical data. Quantum computing, on the other hand, brings exceptional computational power that excels in solving optimization problems, which becomes especially useful in the later stages of clinical trials where logistical and resource allocation decisions have significant impacts on outcomes and costs.

Our solution transforms clinical trial design by integrating Quantum with AI, optimizing both patient selection and trial parameters such as dosage, scheduling, site selection, etc. By analyzing vast datasets, our AI component identifies the most suitable trial candidates swiftly, ensuring rapid enrollment. Then our Quantum computing component takes over to address the intricate task of trial design optimization that manages a highly complex set of variables to allocate trial resources most efficiently for the highest safety outcomes.

When Quantum + AI are applied together, we can achieve significant advancements in clinical trials:

• Faster Development of Lifesaving, Life-Extending, and Life-Changing Treatments: Reduced trial times mean new therapeutics safely reach patients sooner, potentially saving countless lives.
• Reduced Healthcare Costs: Streamlined trials lead to significant cost savings for pharmaceutical companies, government-supported R&D, and healthcare delivery, improving overall healthcare affordability.
• Broader Patient Access to New Therapies: More efficient trials open doors for wider patient participation and greater compliance, ensuring groundbreaking treatments reach those in need. We also expect there to be greater precision in determining the ideal patient profile (and risk profiles) for certain treatments.
• Beyond Efficiency: Superiority in patient selection, trial safety, and design.

Our Hybrid Quantum + AI approach can go beyond traditional computing methods by offering:

• Unmatched Precision: We ensure trials target the ideal patient population, minimizing risks and maximizing effectiveness.
• Unparalleled Efficiency and Scalability: Our solution tackles even the most complex research challenges with exceptional speed and scalability.'

This dual Quantum-AI approach is projected to significantly improve clinical trials. By potentially reducing recruitment time by 20-30% and overall trial time by 15-25%, it has the potential to unlock cost savings of 20-30% and expedite the development and availability of life-saving treatments.

Security Architecture and Patient Privacy

In our commitment to safeguarding patient information, our system's architecture is designed with robust security measures that prioritize patient privacy above all else. Functionality within our secure framework ensures that all data, particularly sensitive patient information, is handled with the utmost care throughout the analysis process. Before any data is processed, it undergoes a thorough anonymization procedure, ensuring that patient identities remain confidential while still permitting the extraction of valuable medical insights. This approach not only protects individuals' privacy but also builds a foundation of trust and security in our healthcare data operations.

Quantifying the Opportunity: Market Size for Quantum-AI Solutions in Clinical Trials

The market potential for Quantum-AI solutions in clinical trial optimization is significant and multifaceted. Here's a breakdown of the key market segments and their estimated sizes:

The current clinical trial landscape faces a significant challenge: lengthy and expensive trials that hinder the development of life-saving treatments. This is where Quantum-AI solutions come in, offering a powerful approach to streamline and optimize this process. Here's a breakdown of the substantial market opportunity for our technology:

Target Customers and Market Segments:

• Pharmaceutical & Biotech Market (Market Size: ~$1.3 trillion): These companies grapple with high R&D costs due to extended trials. Our solution offers faster development cycles and significant cost savings, translating to a potential market opportunity of $65 billion annually by capturing a conservative 5% of R&D savings.
• Contract Research Organizations (CROs) (Market Size: ~$50 billion): CROs manage trials for pharmaceutical companies and are increasingly adopting innovative solutions. Our software provides them with a competitive edge through faster and more efficient trial execution, representing a potential $5 billion annual opportunity with a 10% market share capture.
• Academic Medical Centers & Research Institutions (Market Size: ~$80 billion research funding): These institutions conduct a sizable portion of clinical trials and face pressure to secure funding and expedite results. Our software optimizes their trial designs, leading to a potential $4 billion annual opportunity by capturing 5% of research funding dedicated to clinical trials.

Growth Potential:

The global clinical trial market is projected to reach $70.7 billion by 2027, indicating a growing demand for innovative solutions like ours. By capturing a significant share of this rapidly growing market, our Quantum-AI software solution is poised to become a dominant force in the future of clinical trial optimization.

Call to Action

Increase your speed, efficacy, and safety in your clinical trials with Artificial Brain's Quantum AI Hybrid solutions. Reduce operational costs, expedite development timelines, reduce human subject risk, and bring life-saving treatments to patients faster. Connect with Jitesh Lalwani or Dana Linnet to learn how our innovative technology can transform your clinical research trials.

About Artificial Brain

Artificial Brain is a quantum computing company specializing in real-time software for extremely complex optimization problems in Aerospace, Defense, and Energy, which are beyond the reach of current classical computing alone. With its flagship software 'Planck’, Artificial Brain’s customers are empowered to solve previously unsolvable challenges, leverage greater access to their data, and unlock hidden operational and revenue potential.

Artificial Brain is part of the current cohort of the Hustle US Defense accelerator which is co-sponsored by US AFRL (Air Force Research Lab), National Grid, and New York State.

Artificial Brain is also a winner of The European Union Agency for the Space Programme (EUSPA) MySpace Competition in the Prototype Track, Deep Tech Category. The company proved its quantum software designed for optimizing dynamic Earth Observation Satellite constellation scheduling and optical targeting.?

Artificial Brain has also been featured in Nature India and demonstrated their technologies in collaboration with the Dutch government. These accomplishments underscore the company's commitment to leveraging quantum-based technologies for global sustainability. The article titled "Quantum-based technologies can solve India’s sustainability challenges," is available here .

References:

1. How Much Does It Cost to Research and Develop a New Drug? A Systematic Review and Assessment
2. How long a new drug takes to go through clinical trials
3. Trends in healthcare spending
4. Harnessing artificial intelligence to improve clinical trial design
5. AI-based prediction of clinical drug response
6. Artificial intelligence can improve patients’ experience in decentralized clinical trials
7. Artificial Brain’s benchmarking paper
8. Artificial Brain’s peer-reviewed paper on location optimization for EV chargers can be modified for optimal site selection for clinical trials
9. Quantum computers can solve combinatorial optimization problems more easily than conventional methods, research shows

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