Leveraging Artificial Intelligence in Clinical Trial Workflows
Developing new drugs is a challenging process that takes around 10-12 years and $1.2 billion on average. Only a small percentage of drugs make it to the clinical trial phase. Even then, FDA approval is not guaranteed.
These challenges make it crucial for pharmaceutical companies to optimize their processes. One way they can do that is by leveraging artificial intelligence (AI) in clinical trials. With robust compliance safeguards, AI can help with many aspects of the clinical trial process. Today, we will delve deeper into the benefits of utilizing AI for workflow automation.
Incorporating AI in Clinical Trials
AI is revolutionizing the future of clinical trials. Here are some ways biopharma companies are using this technology in their operations.
Patient Recruitment
Patients are fundamental to the heart of clinical trials. Recruiting patients for a study is a time-consuming task. 85% of trials don’t even succeed in enrolling enough patients to begin trials.
By using artificial intelligence in clinical trials, users can intelligently sift through vast collections of candidates and quickly narrow down the most qualified ones for their trials based on the specific needs, purpose, inclusion criteria, and exclusion criteria.
Training & Study Assistance
Another area to leverage artificial intelligence in clinical trials is for tailored assistance to sponsor, CRO, and site users across a wide range of trial content.
By utilizing powerful generative models and providing accurate context tailored for each individual user, AI can answer a wide variety of questions related to study content. For example, site users are generally trained in multiple study tasks, which can include many nuances for each procedure that is required to be carried out. An AI assistant with proper compliance guardrails can seamlessly answer questions regarding these procedures, provide the exact document(s) it referenced, and ensure no external information was used to hallucinate responses.
Trial Design
AI is also helping companies optimize their trial designs by:
Analyzing data patterns
Predicting patient behavior
Predicting drug efficiency
Researchers use this information to identify suitable patients and determine the optimal treatment regimens.
Data Collection
AI tools collect and analyze data automatically. Biopharma companies are leveraging this feature of AI to collect data from health surveys and electronic records.
This capability of AI allows for more accurate data analysis and workflow automation.
Advantages of Leveraging AI in Clinical Trials
Besides simplifying clinical trials, AI technologies have the following advantages.
Cost Savings
AI can significantly reduce costs and save time by automating essential processes like:
Safety monitoring
Patient enrollment
By streamlining these processes, AI allows study teams to allocate their resources to more important factors in the trial.
AI-powered predictive tools further aid in resource allocation decision-making. This advantage contributes to the overall cost-effectiveness.
Enhanced Data Analysis
Studies show that implementing artificial intelligence in clinical trials can improve data analysis accuracy and efficiency.
For instance, AI algorithms can look through extensive databases of chemical compounds to pinpoint those that can bind to a specific target. They can also predict the toxicity of a compound and avoid adverse events. These capabilities of AI lead to higher-quality research and more accurate results.
Additionally, using artificial intelligence in clinical trials allows study teams to analyze these factors and detect the patient population most likely to benefit from a drug. From there, AI algorithms can determine personalized dosages and treatment frequency.
Accelerating Development Timelines
Workflow automation can significantly expedite the process. AI solutions can lead to faster drug development by:
Enhancing site collaboration
Eliminating redundant efforts
Identifying suitable trial participants
Automating time-consuming and labor-intensive tasks
Better Patient Outcomes
Lastly, AI tools can improve patient outcomes by:
Detecting high-potential candidates
Predicting adverse reactions
Refining trial design
Enhancing safety monitoring
In addition, AI-driven wearable devices can allow for real-time patient monitoring. This feature gives study teams more insight into patient responses and enables timely intervention.
Artificial Intelligence in Clinical Trials with InnovoCommerce
Start taking advantage of AI solutions with InnovoCommerce’s industry-leading Innova AI solution, which can be applied on an enterprise scale to clinical study documents.
We have the most comprehensive enterprise investigator platform trusted by some of the world’s top pharma companies. Our software can automate workflows, streamline compliance, and enable remote monitoring.
Contact us today and request a demo to enhance your research quality!