The healthcare industry has evolved a lot, thanks to the advent of AI.
But what AI has truly helped in is automating the painstakingly lengthy process of rare disease treatment.
How so?
Because there are approximately 7,000 rare diseases affecting about 300 million people across the world! Most importantly, there is a serious lack of skilled resources to carry out the huge trial-and-error process that comes before a new drug hits the market.
AI-powered drug discovery has finally filled this huge crevice. In fact, at Web Summit Qatar, Alex Aliper, president of Insilico Medicine, proposed the development of a ‘pharmaceutical superintelligence,’ which can be used to handle several drug discovery tasks simultaneously, with unparalleled accuracy.
So, what’s the future of AI-based rare disease treatment looking like? Let’s explore the blog to learn more.
Minimizing the Diagnosis Phase
For patients suffering from rare diseases, like ALS or Gaucher disease, one of the greatest issues is the diagnosis phase.
What happens is, primary care doctors aren’t exactly rare-disease experts, and therefore, a successful diagnosis at times can take anywhere from 5- 7 years! And this is where the shortage of labor hits the hardest. Such patients usually move from one specialist to another, with the risks of misdiagnoses along the way.
But we are seeing incredible breakthroughs in how AI is influencing rare disease treatments. AI algorithms can now scan millions of electronic health records (EHRs), and identify the most subtle symptoms that might be missed due to human errors. This way, it becomes easier to detect potential rare conditions earlier, which ensures patients get to the right experts at the initial stages.
Bridging the Gap in Research
The labor issue isn’t just a clinical problem, but a laboratorian problem as well!
The creation of a new drug, that too, for a rare disease, is expensive and highly labor-intensive. Previously, a single drug-discovery project required a team of chemists and biologists, who manually tested thousands of compounds before coming up with the perfect solution.
However, in 2026, the use of AI for rare disease detection has turned the tables. Insilico’s recently-launched ‘MMAI Gym’ helps train LLMs like ChatGPT or Gemini to handle such tasks. Aliper’s goal is to build a multimodal and multitasking model, which can solve several drug discovery tasks accurately..
Commenting on the importance of this innovation, Aliper states, “We really need this technology to increase the productivity of our pharmaceutical industry and tackle the shortage of labor and talent in that space, because there are still thousands of diseases without a cure, without any treatment options, and there are thousands of rare disorders which are neglected.”
Other than that, AI and robotics have also paved their way into niches like dental implants, which have become quite popular in today’s day and age.
AI with Gene-Editing Technologies
The Co-founder and CEO of GenEditBio revealed that they are working on the second phase of their CRISPR technology, which has shifted from editing cells outside the body (ex vivo), and is moving toward editing cells within the body (in vivo).
How will that work?
Well, with the help of their proprietary engineered protein delivery vehicles (ePDVs), they will transfer gene-editing tools directly to the affected cells or tissues.
Along with that, their NanoGalaxy platform serves as a GPS, which will help track these ePDVs. The platform’s AI will scan through these nanoparticles and check which of the chemical structures match the specific body parts (like eyes or the nervous system).
After the initial observation, the AI suggests some basic tweaks in the ePDV’s structure to make sure it reaches its targeted cell/ tissue without triggering the immune system.
That’s another one of the breakthroughs that is set to revolutionize the treatment of rare genetic diseases like Cystic Fibrosis or Alport Syndrome!
What does the Future Look Like?
With the recent developments that AI has brought about, we are looking forward to the days when these rare diseases will no longer be a hurdle to the overall quality of care.
Having said that, the future of AI in biotech looks quite promising, thanks to how it is managing the tedious trial-and-error process! AI is quietly becoming the supercharged assistant that every researcher and scientist would love to work beside in a lab, as it is helping to:
- Summarize volumes of research material and help scientists stay updated on global breakthroughs.
- Locate candidates for clinical trials by analyzing massive data sets, which is by far one of the most labor-intensive tasks of rare disease research.
- Minimize the overall diagnosis delays, thereby reducing misdiagnoses.
- Automate trial-and-error phases to significantly reduce the overall time that manual labor might take to come up with a new drug.
Therefore, artificial intelligence in healthcare is not just a trend, but a forced multiplier that is going to ensure that no patient gets left behind due to the shortage of labor.
Also, if you like to stay updated and share such breakthroughs in healthcare, The Healthcare Facts might be the platform you’re looking for! Send your blogs under their write for us healthcare category to get featured!
F.A.Qs
- How does AI drug discovery speed up the diagnosis of rare diseases?
AI automates the process of data analysis from multiple sources and helps identify hidden patterns and diseases in a matter of moments. This is quicker than those manual processes, which took months or even years to complete.
- Will AI be replacing the role of lab scientists?
No. AI can automate the process, but it still requires human validation and interpretation. So, AI won’t be replacing lab scientists, but can certainly be the smart assistant working beside them!
