Adult hugging child

The summer of 2009 was a nightmare for my family. Our 3-month-old son Sergio was ill, and doctors could not diagnose his condition. Our family went on a long journey to find an answer. Two years after his symptoms began, in 2011, we learned that he had Dravet Syndrome.

Neurologists were working to find a diagnosis and Sergio was being treated while they searched. At nine months of age, he was given a drug that was contraindicated for what ultimately was his condition. Soon after receiving it, he started to have dozens of seizures per day.  We stop counting the seizures, and wondered why, in the age of computers, neurologists don’t use computers and data to improve the diagnosis process.

This event changed my life. I founded the Dravet Syndrome Foundation in Spain in 2011 after learning of Sergio’s condition, and later, Foundation 29. I spent seven years trying to find a cure. Unfortunately, finding a cure for a rare disease is very challenging. Instead, using resources available to me as a Microsoft employee, and with foundation volunteers, created a diagnostic program for children with Dravet Syndrome, called Dx29. To date, it has provided diagnoses for more than 700 patients worldwide. It is now available for clinicians to use free of charge.

The Long Wait for a Rare Disease Diagnosis

Patients live an average of 4.8 years for a rare disease diagnosis. In the meantime, they contend with the risk of medical errors and severe side effects.  Patients visit an average of 7.3 specialists, with 40% of patients reporting that a delayed diagnosis had a significant or very marked impact on their condition. It is estimated that 6-8% of the world is affected by a rare disease, meaning that improvements in diagnosis procedures could impact 460-620 million people.

The Need for Clinical Data Integration

The conventional diagnosis process is not designed for the complex biology behind rare diseases. It usually starts with a clinical consultation. A physician requests a genomic test, sending along the biological samples and the symptoms (phenotypes) already identified. The sequencing is performed and bioinformaticians (often manually) analyze the large amount of data produced. To carry out this complex analysis, they use the symptoms identified by the physician to guide their search.

The physician’s and bioinformation’s data are not integrated, so these professionals are disconnected. Those conducting the gene filtering have partial phenotypic information but are unable to collect more data because only physicians have full access to patients and their records. The genetic report the physician receives would likely be different if more patient information was available during gene filtering. Clinical decisions made based on the genetic data could be different with more data. How can bioinformaticians check if a given gene variant in the patient is producing a concrete phenotype? How is the patient information put in the hands of bioinformaticians? There is an information gap issue.

Satya Nadella Empowers Employees to Help

At the 2017 Microsoft employee hackathon in Spain, one of my best friends, and Microsoft colleague, Sacha Arozarena, suggested we create a bot to diagnose patients with rare diseases. After just three days of intensive work, our prototype was able to suggest symptoms and navigate the user to a potential diagnosis. It was still a proof of concept, but we won the Spanish hackathon. The most important achievement of this work was the connections the prototype created for us.

That same month, I heard Satya Nadella discuss his son’s medical condition while he presented at Microsoft Ready, so I sent him an email asking for help. He replied within five minutes, connecting me with Microsoft’s Research team. Through this connection, I learned about Microsoft’s efforts in several areas:  a new Genomics team, a team working on medical natural language processing, and the company’s investments and efforts towards bringing artificial intelligence to health science.

Using the Cloud and AI to Speed Diagnosis

One year ago, colleagues and I founded Foundation 29, a non-profit organization with the mission to improve the lives of patients with rare diseases through faster, better diagnosis. The foundation is developing solutions to facilitate diagnosis, with the intention of distributing them to every physician in the world. Dx29 is the name of this effort. The goal is to reimagine and democratize diagnosis.

The tool we developed uses Artificial Intelligence (AI) to close the information gap. The gene filtering of most routine low-level cases can be automated with AI, allowing bioinformaticians and specialists to focus on the most challenging cases where human intervention is required. Physicians can drive automatic genetic analysis simply by identifying symptoms in the tool. The physician’s role comes back to the center of the process, focusing on the patient and doing symptom identification and differential diagnosis.

Dx29 does not make a diagnosis, but enhances the physicians’ skills. It gives physicians a tool that augments their capabilities by hiding the complexity of genomics and allowing them to focus on clinical diagnosis, something they are already experts on.

The process starts by performing automatic symptom identification and codification from medical records. It then allows physicians to navigate the complexity of gene identification by simply selecting identified symptoms in the tool.  In the final step, once enough symptoms have been matched with the genetic information, Dx29 presents a ranked list of potential conditions for the physician to further evaluate and decide how to proceed. The foundation did the first medical tests last December with promising results. Our goal is to make the tool available to the medical community this spring and find a business model to secure the continuity of the project.

Thanks to Microsoft and Global Organizations

Dx29 is possible because of help from Microsoft and its employees. It is impossible to list all Microsoft employees who joined forces to collaborate on this initiative. Foundation 29 and in particular, Dx29 are honored by the privilege of working with Microsoft software engineers, product groups, and consultants. Architects from Microsoft Services, data engineers, data scientists and the legal department provided us with advice on privacy and data protection.

I am proud to work for a company that empowers employees to achieve more. A lack of diagnosis is not only a stressful situation for patients and families, but also for healthcare professionals. Without a diagnosis, an appropriate treatment is not possible. With all the help received so far, Foundation 29 aims to empower physicians with the right tool to provide an accurate diagnosis.

I would like to thank the following organizations for their contributions to the development of the Dx29 tool and its pilot:

  • Centro de Investigación Biomédica en red de Enfermedades Raras (CIBERER), Madrid, Spain
  • Hospital La Paz de Madrid, Madrid, Spain
  • NIMGenetics, Madrid, Spain,
  • Idibell, Barcelona, Spain
  • The Global Commission on Rare Diseases

Rare disease patients are exceptions in clinical routines, but they drive the medical community towards precision medicine. Precision medicine should not be limited to exceptional cases, but spread to all patients, improving the standard of care for all.

Time is ticking. I know I won’t be able to find a cure for Sergio and he will have to live with Dravet Syndrome all his life. But having the possibility of creating a tool to speed up and improve diagnosis process for other children is a strong motivation for me, my family and the community around us. Helping others is sometimes the only way to heal your own wounds.

Learn more about Dx29, the Global Commission and how AI can support diagnosis and read more from the Microsoft In Health Blog on the Global Commission.