Can AI Help Lower Prescription Costs?

Due to rising medication costs, many patients are forced to abandon their treatments. Additionally, the significant lack of cost-related information continues to limit healthcare workers from prescribing alternative and more affordable medication to patients. The medical industry is beginning to explore artificial intelligence (AI) as a powerful tool to address this issue.

Incorporating AI might become a game changer in reducing prescription costs.

How AI Is Influencing Prescription Decisions

AI is now being used across various sectors, and the healthcare industry is no exception. Leveraging artificial intelligence holds the potential to streamline drug development, influence prescription decisions, and improve patient adherence to medication — all of which can significantly lower the financial burden on patients.

This technology also benefits side-effect prediction and clinical success rate improvement. AI-powered systems can now suggest medications that align with patient budgets and treatment goals. Working similarly to online product recommendation algorithms, these enhanced systems can offer lower-cost alternatives in real time, aiding healthcare providers to make more cost-effective choices for patients.

1. Accelerating Drug Development With AI

In traditional drug development, lengthy timelines and high costs go hand in hand. However, the pharmaceutical industry is witnessing generative AI to revolutionize this process, making AI-enabled drug discovery a reality.

Advanced algorithms like artificial neural networks and support vector machines (SVMs) are among the AI algorithms used in drug design and discovery. When paired with Computer-Aided Drug Design (CADD), massive datasets are analyzed, and drug targets are identified much faster. This shortens the long periods of the analysis phase as potential drug candidates are now identified more quickly. In turn, the prices of newly introduced drugs to the market decrease.

2. Predicting Drug Interaction and Side Effects

AI tools are also becoming more sophisticated. They can more precisely and effectively predict potential drug interactions and side effects through molecular data, electronic health records, and large-scale data.

For example, IBM’s Watson for Health uses AI to assess drug interactions and recommend safer and more effective prescription options. By preventing complications that may require additional treatments, artificial intelligence lowers the risk of unexpected healthcare expenses.

3. Improving Success Rates in Clinical Trials

Clinical trials are expensive, and high failure rates can drive up the cost of new drugs. AI addresses this by improving clinical trial matching, patient monitoring, and overall trial design — all of which reduce operational expenses. 

By harnessing generative AI to enhance predictive accuracy in drug design, pharmaceutical researchers can better assess a new drug’s potential efficacy, reducing risks during clinical phases and other related costs.

4. Recommending Cost-Effective Prescriptions

Studies show that when healthcare providers have access to real-time price comparisons, they are more likely to offer affordable options for their patients. A study by FIU Business found that healthcare professionals frequently selected lower-cost alternatives when price data was available through an AI-powered recommender system.

AI systems can also be programmed to prioritize prescription affordability, thus enhancing patient adherence to medication. These tools hold significant promise for reducing healthcare costs and ensuring effective patient care.

5. Saving Medical Expenses With HSA

Health Savings Accounts (HSAs) allow patients to save pre-tax dollars for healthcare expenses, and AI can be instrumental in making those savings stretch further. 

By recommending cost-effective prescription options and predicting adherence challenges, artificial intelligence helps patients maximize their healthcare funds, ultimately reducing their out-of-pocket expenses.

6. Expanding Personalized Medicine Options

Artificial intelligence can also pave the way for customized medications that align with each patient’s unique needs. For instance, AI can help identify drugs most effective for an individual’s genetic profile, thereby reducing the trial-and-error phase of medication. 

Genomic-based AI platforms are already used in oncology to identify drug candidates specifically suited to a patient’s cancer type. This approach minimizes the side effects and can lead to more successful outcomes at lower costs by avoiding high-cost, one-size-fits-all treatments.

Cost-Effective Care Is Within Reach with AI

With AI’s growing capabilities, the potential to lower prescription costs is indeed becoming a reality. By playing a fundamental role in drug discovery and tailored prescriptions, AI helps reduce patients’ financial burden. As this technology continues to evolve, effective, affordable, and individualized healthcare may soon be at hand for more patients.