Forging a novel therapeutic path for patients with Rett Syndrome using AI

Good news! The AI doctor is in the house! This is only the beginning!

This seems to be a great example where AI can make huge difference in finding a cure for a very rare and complex disorder.

AI identified a FDA-approved drug to treat Rett Syndrome.

"Rett syndrome is a devastating, rare genetic childhood disorder primarily affecting girls. Merely 1 out of 10,000 girls are born with it, and much fewer boys. It is caused by mutations in the MeCP2 gene on the X chromosome, leading to a spectrum of cognitive and physical impairments, including repetitive hand motions, speech difficulties, and seizures.

However, besides severe impairment of neurological functions, which has been the primary focus of researchers, Rett syndrome also upsets the functions of many non-neurological organs, including the digestive, musculoskeletal, and immune systems. This complexity has made the development of an effective cure able to treat the disease across multiple tissues an extreme challenge. ..."

From the abstract and plain language summary:

"Background

Many neurodevelopmental genetic disorders, such as Rett syndrome, are caused by a single gene mutation but trigger changes in expression of numerous genes. This impairs functions of multiple organs beyond the central nervous system (CNS), making it difficult to develop broadly effective treatments based on a single drug target. This is further complicated by the lack of sufficiently broad and biologically relevant drug screens, and the inherent complexity in identifying clinically relevant targets responsible for diverse phenotypes that involve multiple organs.

Methods

Here, we use computational drug prediction that combines artificial intelligence, human gene regulatory network analysis, and in vivo screening in a CRISPR-edited, Xenopus laevis tadpole model of Rett syndrome to carry out target-agnostic drug discovery.

Four-week-old MeCP2-null male mice expressing the Rett phenotype are used to validate the therapeutic efficacy.

Results

This approach identifies the FDA-approved drug, vorinostat, which broadly improves both CNS and non-CNS (e.g., gastrointestinal, respiratory, inflammatory) abnormalities in X. laevis and MeCP2-null mice. To our knowledge, this is the first Rett syndrome treatment to demonstrate pre-clinical efficacy across multiple organ systems when dosed after the onset of symptoms.

Gene network analysis also reveals a putative therapeutic mechanism for the cross-organ normalizing effects of vorinostat based on its impact on acetylation metabolism and post-translational modifications of microtubules.

Conclusions

Although vorinostat is an inhibitor of histone deacetylases (HDAC), it unexpectedly reverses the Rett phenotype by restoring protein acetylation across hypo- and hyperacetylated tissues, suggesting its activity is based on a previously unknown therapeutic mechanism.

Plain language summary

Traditional drug discovery platforms focus on singular targets and take several years to validate treatment efficacy before entering clinical trials.

Here, we describe a discovery platform that leverages artificial intelligence (AI) and gene expression profiles in combination with a genetically engineered tadpole and mouse models of a form of autism, known as Rett syndrome, to identify an existing FDA approved anticancer drug (vorinostat) that may be repurposed as a treatment for this condition. We show that vorinostat improves both the neurological and non-neurological symptoms of Rett syndrome in both models. Analysis of vorinostat’s therapeutic action reveals that internal structural elements in cells, known as microtubules, represent a suitable target for treatment of this disease. This AI-based computational discovery platform demonstrates the possibility of rapidly identifying alternative uses for existing FDA approved drugs for treatments of patients with complex genetic disorders."

Forging a novel therapeutic path for patients with Rett Syndrome using AI "AI-enabled drug discovery approach identified potentially game-changing treatment, which has been advanced from the lab bench to an FDA Orphan Drug Designation in record time"

AI-enabled drug prediction and gene network analysis reveal therapeutic use of vorinostat for Rett Syndrome in preclinical models (open access)

Fig. 2: Network-based computational prediction of effective drugs to treat Rett syndrome in tadpole models.

Repurposing Old drugs with AI

This kind of repurposing has been a very exciting approach for decades!

This survey article below does not even seem to care for machine learning and AI very much although ML & AI are going to revolutionize drug repurposing in a major way unlike what was done before.

In a recent article, the New York Times also described how ML & AI are aiding drug repurposing (see below).

"Developing a new drug for a disease is a lengthy and expensive process, so researchers are increasingly turning to existing drugs — some of which have never been approved — to see if they can treat diseases other than the ones they were designed for. The speed at which drugs can be repurposed made this a popular strategy during the COVID-19 pandemic, when drugs such as the corticosteroid dexamethasone and the rheumatoid arthritis drug baricitinib were used to treat severe cases of the disease. Now, a review has compiled a list of hundreds of databases and prediction models, including machine-learning algorithms, that can support drug-repurposing studies. But researchers will still need to collect clinical data, such as side effects, when the drugs are used in new ways."

From the abstract:

"Repurposing of existing drugs for new indications has attracted substantial attention owing to its potential to accelerate drug development and reduce costs. Hundreds of computational resources such as databases and predictive platforms have been developed that can be applied for drug repurposing, making it challenging to select the right resource for a specific drug repurposing project. With the aim of helping to address this challenge, here we overview computational approaches to drug repurposing based on a comprehensive survey of available in silico resources using a purpose-built drug repurposing ontology that classifies the resources into hierarchical categories and provides application-specific information.

We also present an expert evaluation of selected resources and three drug repurposing case studies implemented within the Horizon Europe REMEDi4ALL project to demonstrate the practical use of the resources. This comprehensive Review with expert evaluations and case studies provides guidelines and recommendations on the best use of various in silico resources for drug repurposing and establishes a basis for a sustainable and extendable drug repurposing web catalogue."

"In labs around the world, scientists are using A.I. to search among existing medicines for treatments that work for rare diseases. Drug repurposing, as it’s called, is not new, but the use of machine learning is speeding up the process — and could expand the treatment possibilities for people with rare diseases and few options.

Thanks to versions of the technology developed ... at the University of Pennsylvania and elsewhere, drugs are being quickly repurposed for conditions including rare and aggressive cancers, fatal inflammatory disorders and complex neurological conditions. And often, they’re working."

Nature Briefing: Translational Research

Computational drug repurposing: approaches, evaluation of in silico resources and case studies (no public access, but article above contains link to PDF)

Doctors Told Him He Was Going to Die. Then A.I. Saved His Life. "Scientists are using machine learning to find new treatments among thousands of old medicines." (Credits: Human Progress weekly newsletter)

Sammy Basso, a biologist and progeria advocate, has died at age 28

Update: I learnt today (7/8/2024) or my memory was refreshed that many individuals suffering from progeria do not survive teenage years. (Source)

RIP

I don't remember when I first became aware of this man and his rare-disease. Indeed, he seemed to have embraced humor to live his life.

"We generally don’t think of rare-disease advocacy as funny. But of the many qualities apparent to anyone who met Sammy Basso, a biologist and spokesperson for the progeria patient community, who died suddenly on Saturday at 28, perhaps the most disarming was his ability to find laughter in almost anything. One April Fool’s Day, he posted a video about his doctors putting him on a diet — an absurdity for someone whose genetic disorder prevented him from gaining weight. “A seafood diet. When I see food, I eat!” he said, pressing a button for a ba-dum-tss, grinning into the camera. ..."

How Sammy Basso’s short life changed rare disease research | STAT