The number of novel AI-developed hair loss products keeps proliferating. The latest one is South Korea based LG AI Research and its AI-developed Rhamsydil. It is a cosmeceutical type product, so there will be no need for it to go through any clinical trials. In fact the company plans to release Rhamsydil in 2026.
Rhamsydil: LG’s AI-Driven Hair Loss Solution Set to Launch in 2026
LG (a multinational conglomerate) via LG AI Research has used artificial intelligence (AI) to develop a novel compound called Rhamsydil to treat hair loss. The main ingredient activates a key estrogen receptor on the scalp. The company presented its new AI-developed products at last week’s International Conference on Machine Learning (ICML) in Seoul (video at the bottom). ICML is one of the world’s three most prominent AI and machine learning conferences per Korea Herald.
LG created Rhamsydil using its flagship AI model EXAONE. Their EXAONE Discovery platform is designed to accelerate the discovery of advanced materials and drug candidates. Rhamsydil was discovered by LG Household & Health Care in collaboration with LG AI Research. The latter used AI to screen more than 420,000 candidate compounds in just one day. Per the company:
“The ingredient has demonstrated hair-loss prevention efficacy without steroid-derived compounds.”
The research behind this product was presented at the 14th World Congress for Hair Research that was held in South Korea in May 2026. Rhamsydil is being prepared for commercialization in 2026.
Estrogen Receptor Activation and DKK-1 Inhibition
On Linkedin, LG Household & Healthcare makes the following claim:
“Using AI-powered screening on around 420,000 candidate molecules, LG H&H identified a vitamin A–derived, non-steroidal ingredient that can activate a key estrogen receptor linked to women’s hair health. In testing, this ingredient helped create a more favorable environment for hair growth, supporting both hair follicles and their stem cells, and showed visible improvements in hair thickness in clinical evaluation. Rhamsydil has been shown in lab studies to help reduce signals that push hair into the shedding phase, pointing to its potential as a next-generation “scalp longevity” ingredient.”
Since its inception in December 2020, LG AI Research has published 363 papers at the world’s leading AI conferences. The institute has also to date filed 838 patent applications (371 domestic patents, 243 international patents and 224 PCT applications),
Per Lim Woo-hyung (the co-director of LG AI Research), EXAONE has evolved into an expert AI system that delivers real-world solutions. It is poised to claim global AI leadership through a first mover strategy and a pioneering approach to solving complex industrial challenges.
Using artificial intelligence (AI) and machine learning (ML) for hair loss drug discovery.
In the past, I briefly discussed the use of artificial intelligence (AI) and machine learning (ML) in drug discovery. Especially when it comes to the potential of rapidly testing new compounds to treat hair loss. Funding for drug discovery startups that use AI is now really taking off. Heavyweight companies such as Amazon, Anthropic, Google and Palantir increasingly focusing in this area. However, the AI drug boom is still in its early stages.
Note that this post was originally written in November 2022, but needed an update due to a many new developments.
Hair Loss Companies using AI to Develop new Drugs
A number of hair loss companies are currently developing new drugs via the use of AI. I will update this section regularly.
The most widely covered of these is Absci (US), an artificial intelligence drug and biologic creation company that is developing novel treatments via the use generative AI. Their most anticipated product is a prolactin receptor (PRLR) targeting injection based hair growth treatment called ABS-201. It is in Phase 1 clinical trials as of 2026.
In 2026, LG AI Research (South Korea) announced that it had developed a new hair loss cosmeceutical using AI. The compound is called Rhamsydil and it is expected to be released into the market by the end of 2026. The company’s AI technology screened over 420,000 candidate compounds in just one day before finding and developing Rhamsydil. It consists of a vitamin A–derived, non-steroidal ingredient that can activate a key estrogen receptor on the scalp.
Also in 2026, a start-up named RE:YOU claimed to have developed four new molecules to benefit hair growth using AI.
A few years ago, there was much hype about a new AI drug discovery company named Insilico Medicine (Hong Kong). Among the conditions the company aimed to develop drugs for included hair loss. While they mentioned hair in a number of their past press releases, you no longer see it on their pipeline page. Update: Eli Lilly (US) and Insilico struck a $2.75 billion AI drug discovery deal in March 2026. And Takeda (Japan) and Insilico struck a $600 million AI drug discovery deal in July 2026.
A new Chinese company called 01 Life Technology is using AI to create a microbiome database and discover new molecules to treat various skin conditions, including hair loss.
Another hair loss company making use of AI is South Korea’s Epibiotech. In October 2021, it signed an agreement with CN.AI (South Korea) in order to accelerate the discovery of new hair loss drug candidates.
Also of interest, in December 2019, Iktos (France) and Almirall (Spain) signed an agreement in which Iktos’ AI modelling technology would be used to design novel optimized compounds for Almirall. The latter is a company that is entirely focused on skin and other dermatological conditions. They currently make the world’s only topical finasteride product that has undergone rigorous clinical trials.
Using AI to Predict Hair Loss Compounds
What made me first write this post was an interesting article titled: “Researchers use AI to predict compounds that could neutralize baldness.” The actual study from China is here and it was published on October 20, 2022.
In the article, they mention that male pattern hair loss is caused by androgens, inflammation or an overabundance of reactive oxygen species. One potential treatment for the last mentioned is via the creation and utilization of “nanozymes” that mimic the superoxide dismutase (SOD) enzyme. SOD helps fight damaging oxygen free radicals.
The scientists tested machine-learning models with 91 different transition-metal, phosphate and sulfate combinations. A highly efficient manganese thiophosphite (MnPS3) based SOD mimic was discovered using machine learning tools. These ML techniques predicted what cobination would have the most powerful SOD-like ability.
The team subsequently prepared MnPS3 microneedle patches which they used to treat androgenic alopecia-affected mouse models. Microneedling allowed the MnPS3 to penetrate deep layers of the skin (where hair follicle stem cells reside) and remove the excess reactive oxygen species. Within 13 days, the animals regenerated thicker hair strands that more densely covered their previously bald backsides.
Also check out how it is possible to speed up drug discovery with diffusion generative models (such as the DiffDock molecular docking model).
Opensource Databases and Resources
Although not exactly AI, I find the increasing number of online opensource resources, databases, repositories and collaborative research tools encouraging.
Make sure to read my post on the publicly available DeepMind AlphaFold protein database. You can search for “hair” in there and get 2,200 results as of today.
Also of interest are open source sites such as the Driskskell Lab’s skin regeneration and wound healing related datasets.
More recently, Dr. Maksim Plikus and his team at UCI developed CellChat, which enables the better understanding of cell-to-cell communication and signaling.
Other AI Applications in the Hair Loss World
Note that artificial intelligence is also being used for other purposes beside drug discovery in the hair loss world. Among these include:
Fully automated hair growth detection and measurement systems.
New deep learning-based systems used to quantify hair characteristic by scalp area.
Tools to help with hair loss self-diagnosis, including Apps.
New AI Solution to Diagnose Hair Loss Type via Scalp Biomarkers
Cosmetics manufacturer Kolmar Korea (South Korea) has developed an artificial intelligence-based solution that can diagnose hair loss using scalp biomarkers. The technology can diagnose 16 different types of androgenic hair loss (nine male and seven female). A dermatologist collects samples of a patient’s scalp, places them on proprietary analytics equipment, and has the AI-powered tool screen scalp surface biomarkers.
Kolmar Korea expects that its diagnostic tool will help hair loss patients and dermatologists choose optimized treatments. The company also plans to develop various cosmetics that target each of the 16 different types of androgen related hair loss.
