Adipose-Derived Stem Cells (ADSC), Cell Therapy, Dermal Papilla Cells, Dermal Sheath Cup Cells, Hair Regeneration

Effective Cell Therapy for Hair Regeneration

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Update: Epibiotech CEO Sung (who is the author of the new paper covered in this post) is answering our questions in the comments this week. Please note that English is not his first language.

Earlier this month, Epibiotech CEO Jong-Hyuk Sung published a detailed new paper titled “Effective and economical cell therapy for hair regeneration.” It was widely covered in South Korean media (h/t “Theo”, who also sent me this update on Mr. Sung’s presentation covering the paper). They call him Seong Jong-Hyeok in that article.

My interest piqued when I read such a thorough scientific paper from a CEO (almost unheard of in this industry). I showed it to a well known hair transplant doctor, and he found it to be a great summary. I also e-mailed one of Epibiotech’s media representatives with some questions, but no response so far.

Adipose, Dermal Papilla and Dermal Sheath Cells

Note that Dr. Sung has publiched numerous papers on adipose-derived stem cells (ADSC) and hair regeneration (and wound healing) for 15 years. This CEO seems to be a scientist first and foremost, rather than a business person.

This latest paper covers the three main types of cell based hair regeneration treatment strategies that are currently being developed:

  1. Adipose-derived stem cells (ADSC or ASC).
  2. Dermal papilla cells (DPC).
  3. Dermal papilla epithelial cup cells, better kown as dermal sheath cup cells (DPSC or DSC).

The paper also mentions the manufacturing of hair organoids using induced pluripotent stem cells. Including a shout out to Dr. Takashi Tsuji.

  • Note that Shiseido (including its use of Replicel’s technology) is working on a hair regeneration treatment involving culturing of dermal sheath cup cells. More details here.
  • Also note that in the past, Aderans and Intercytex both saw some success in hair growth via dermal papilla cell culturing and injection into balding scalps. HairClone is currently trying something similar.

Dr. Sung’s company Epibiotech is ultimately driven by “Off-the-shelf” allogeneic DPC therapy. It aims to begin Phase 1 clinical trials for its EPI-001 dermal papilla cell hair multiplication treatment in 2023. We are all hopeful that things will move faster in Asia in comparison to the US or Western Europe. The company can already mass-produce dermal papilla cells with hair growth ability using spheroid culture, hypoxic conditions, and growth factors.

Cell Therapy Hair Growth
Cell therapy for hair growth. Adipose, dermal papilla and dermal sheath cup cells. Source: Biomedicine & Pharmacotherapy, January 2023.

Adipose Derived Stem Cells

Given the author’s background, the paper is especially detailed when it comes to ADSC (ASC). Dr. Sung highlights the pros and cons.

    • Adipose-derived stem cells are easy to access and isolate in large quantities. This is not true when it comes to dermal papilla cells and dermal sheath cup cells.
    • While ASCs promote hair growth through the paracrine effect, they have a poor potential in hair neogenesis. Dr. Sung suggests further development in methods to enhance the trichogenecity of ASCs.

Other New Studies on Hair Regeneration

As if this was not enough, two new papers on hair regenearation came out in the past month.

  • A lierature review from Japan coveres numerous cell therapies for hair regrowth. This includes mesenchymal stem cell (MSC) implantation. Adult sources of MSC include: adipose tissue (including SVF); bone marrow; DPC; DSC; placenta and umbilical cord. The paper also analyzes non-cell therapies, including exosomes, extracellular matrix, platelet-rich plasma, and the MSC secretome. The last mentioned “comprises bioactive materials, such as growth factors, cytokines and nucleic acids that play an important role in regulating the hair follicle cycle and regeneration”.
  • A new study from China on microenvironmental reprogramming of human dermal papilla cells for hair follicle tissue engineering.
  • And finally, a recent video on regenerative medicine for hair loss starring Dr. Jerry Cooley (interviewed by Dr. Robert Haber).
Artificial Intelligence, Machine Learning

AI and Machine Learning for Hair Loss Drug Discovery

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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.

Update: June 20, 2024

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.

Update: March 31, 2023

Speeding up drug discovery with diffusion generative models such as the DiffDock molecular docking model.

November 4, 2022

Using AI to Predict Hair Loss Compounds

Recently, “Lorence” posted an interesting link to an article that is 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.

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.

Insilico Medicine

Several years ago, there was much hype about a new AI drug discovery company named Insilico Medicine. 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.

Neither is it mentioned in a very recent interview with their CEO. The company was covered in the below 2020 video on artificial intelligence for hair loss.

Other Hair Loss Companies using Artificial Intelligence

Also of interest, in late 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.

Another hair loss company making use of artificial intelligence is South Korea’s Epibiotech (h/t “Ben”). In October 2021, it signed an agreement with CN.AI in order to accelerate the discovery of new hair loss drug candidates.

Opensource Databases and More

Make sure to also read my post on the publicly available DeepMind AlphaFold protein database. 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.

Note that artificial intelligence is also being used for other purposes 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.
  • The ARTAS robotic hair transplant system also uses AI technology when it comes to hair transplants. Only during the graft extraction process for the time being.
  • And as of 2023, the generation of real and fake before and after hair growth photos.