AI in Drug Dosing: Improving Patient Outcomes and Reducing Cost of Care

By Divya Chhabra

Artificial intelligence (AI) is poised to transform chronic disease management by empowering physicians to personalize drug dosing at scale. Dosis, a personalized dosing platform used by dialysis providers to manage chronically administered drugs, has harnessed the power of artificial intelligence to disrupt traditional one-size-fits all dosing approaches, and has introduced precision dosing that is personalized, based on patients’ actual observed responses to their medication. This personalization significantly improves dosing efficiency–achieving equivalent or improved patient outcomes while reducing the cost of care.

Why is now the right time to use AI for dosing?

There are several developments that have come together to create the conditions necessary for the growth of AI-powered drug dosing. The first is technological advancement – modern-day computing power allows for efficient processing of large, complex datasets, making AI solutions practical to implement. 

The second is the general public’s familiarity with artificial intelligence as a tool that can solve complex problems. Public familiarity with a diverse array of AI applications in imaging, consumer electronics, and logistics lend popular credibility to the technology, and allow healthcare providers to be comfortable incorporating such tools in clinical settings. 

The third is the availability of reliable data in a clinical setting – electronic medical records codify and standardize data in a manner that is much more ingestible by algorithms than free-form paper medical records. The accessibility of dosing and outcomes data in electronic medical records and the ability to effectively analyze this data has made applying artificial intelligence and control algorithms to dosing much more practical and efficient. As a result, it is now possible to draw on data from millions of drug doses and their associated outcomes, a vast improvement on previously siloed and inaccessible datasets. 

The final development that cements the need for more innovative dosing approaches is the fact that drugs are now more complex and have more potential to impact basic physiologic processes than at any point in the past. Drugs that impact multiple physiologic processes and have a narrow therapeutic window – the “sweet spot” between toxicity and ineffective therapy – provide the greatest opportunity for  AI-powered dosing.

Dialysis patients and providers significantly benefit from AI-based drug dosing

There are more than 550,000 dialysis patients with End-Stage Kidney Disease (ESKD) in the United States. Dialysis patients tend to have elevated risk for adverse outcomes, and are often on multiple medications. Almost 90% of dialysis patients experience chronic anemia and are treated with Erythropoiesis Stimulating Agents (ESAs). However, exposure to high doses of ESAs is associated with an increase in serious adverse cardiovascular events, like heart attacks and strokes, so the primary clinical intent is to use the minimum amount of medication necessary to prevent patients from requiring blood transfusions.

Dosis’s flagship tool, Strategic Anemia Advisor (SAA), offers dialysis providers clinically validated decision support, empowering them to make optimal dose adjustments based on individual patients’ needs and deliver patient-centered care. It allows clinicians to maintain or improve their hemoglobin outcomes while significantly reducing patients’ exposure to ESAs. This has benefits for both patients and providers: patients are exposed to 25% less drug on average, which means a lower likelihood of serious adverse events like heart attacks or strokes, while providers lower their drug utilization, saving an average $1250 per patient per year. 

 The Future – Chronic Dosing To Be AI-Powered

Dosis has proven that precision dosing at scale is possible, and has established a path to success for future applications of AI within the kidney space, including precision dosing for mineral bone disorder (MBD), expansion of value-based chronic kidney disease (CKD) models, and more.

Over the next decade, partially as a result of Dosis’s innovations, AI-driven dosing models will likely be the standard of care across the chronic care spectrum. In addition, as more tools are developed and more opportunities to use those tools are identified, there will be exponential growth in the use of AI to drive innovative therapies.

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Divya Chhabra is Co-founder and Chief Operating Officer of Dosis. Before starting Dosis, Divya was a Product Manager for B2B and B2C products at athenahealth. She’s passionate about building great products that create a positive change in people’s lives. She received her B.S. in Biological Engineering from MIT.