A jamais jeunes: comment le culte de la beauté a créé un marché de la médecine esthétique à $11Md (article en anglais)

By Maxime Huerre and Francis Turina-Malard, CEPTON Strategies


Looking younger, fitter, and correcting body imperfections: these are the pillars that have been driving the insatiable demand for aesthetic procedures and sustaining the market dynamism over the past few years. In quest for treatments always more “natural” and safer, patients have been increasingly seduced by non-invasive procedures that recently emerged on the market. Formerly reserved to a wealthy population, these less invasive practices and technologies have driven the democratisation of aesthetic medicine toward a younger and broader public. Meeting this demand and diversifying their offer, aesthetic players benefited from a significant and unstoppable growth. But what are the key activities behind such a success?


The Medical Aesthetics, a $11bn market dominated by the US

The International Society of Aesthetic and Plastic Surgery (ISAPS) registered circa 23 million surgical and non-surgical aesthetic procedures worldwide in 2017, for a total medical aesthetics market value estimated at circa $11bn.

From heavy surgeries, such as breast and buttock implants, to less invasive procedures, such as injections or laser-assisted treatments, the demand for aesthetic procedures has been steadily growing over the past few years.

The medical aesthetics market can be divided in four segments:

Figure 1 – Medical Aesthetic market segmentation


Over-represented due to higher prices, the US represents twice the European market, and 50% of the global market value. In Asia, the unformal and hidden practice of aesthetic procedures represents a major obstacle to faithfully measure the demand. Nonetheless, Asia is estimated to represent 20% of the global market and to be the most dynamic geography.

Figure 2 – Market breakdown of medical aesthetics by geography (sources: Cepton analysis based on various market studies)

Facial aesthetics driving the market

A. Facial aesthetics is the largest and well-established segment (half of the global market in value). It is dominated by three generalist companies (Allergan, Galderma and Merz) that have established their positioning through the development of several generations of injectables, from collagen to botox and hyaluronic acid. These products are used for wrinkle correction, facial tissue augmentation and lip enhancement. They are injected by plastic surgeons and dermatologists.

B. Unlike injectables, energy-based devices can be used in various distribution locations such as aesthetic centres, gynaecologists or spas. The broader and easier access to this technology makes it a serious alternative to injections and surgical procedures. Moreover, the complete non-invasive aspect of some energy-based products is an argument to convince patients mistrustful of injectable products and concerned by health hazards of aesthetic products. Nevertheless, energy-based devices have a limited scope of action, mostly skin stimulation functions.

C. Skin tightening and body contouring devices aim to remove body fat excess which cannot be eliminated through natural methods such as exercise or specific diets. Liposuction, the traditional method, is an invasive and painful procedure associated with risks of bleeding, infection or embolism. To limit adverse events, non-surgical treatments have been recently developed and are gaining popularity. For instance, several technologies such as cryolipolysis, laser lipolysis or radiofrequency lipolysis target and naturally eliminate fat cells by using controlled freezing or heating. These technologies cannot be considered as weight loss solutions but can effectively remove stubborn fat excess. Among the invasive procedures, the transfer of autologous fat from an unwanted area to a desired one, called “Brazilian Butt Lift”, has also been experiencing a dynamic 10% growth in 2017.

D. Despite frequent health and sanitary scandals, aesthetic surgical implants are still a growing market. Breast augmentation remain the top surgical procedure, but their number has been stagnating while buttock augmentation is driving this segment growth. The recent international “Implant files” scandal published in November 2018 highlighted severe failures in medical devices monitoring and could act as an impediment to this segment sustainability.

Strong underlying drivers fuelling a sustainable growth

Growing at around 8% per year, the medical aesthetics market is certainly one of the most dynamic markets among the different healthcare specialties. This growth is fuelled by several strong factors.

First, demographic trends steadily contribute to the aesthetic market growth. The worldwide population is continuously growing at +1% per year until 2025 thus logically increasing the target population. Furthermore, the ageing population (over 60 years old) is expected to grow at +3% per year until 2025.

In addition to demographic factors, several societal changes raise the promise of expanding the target population in medical aesthetics.

The first trend is the rising demand for safer, more natural and less invasive aesthetic procedures. In this context, non-surgical procedures have gained popularity and have emerged as a standard transition step between cosmetics and surgery. They largely contributed to the growth of the global aesthetics market and gained momentum over surgical procedures. For instance, in Japan, Brazil and Europe non-surgical procedures have significantly gained market share on the overall number of surgical procedures (see figure 3).

Figure 3 – Penetration of non-surgical procedures in the medical aesthetic market (source: ISAPS Global Statistics 2010, 2016)

On the other hand, women, but also men, are eager to engage in aesthetics procedures younger than ever. Aesthetic doctors and private companies have rapidly adapted to this untapped reserve of patients by luring these new profiles with “beautification techniques”, such as innovative dermal fillers and skin boosting technologies. Convinced by the reversible effects of these products, this younger population has appeared as a new, large, and promising source of growth for medical aesthetics players.

In Asia, beauty standards prove to be slightly different from the ones in the US and Europe. Patients are either looking for skin pigmentation control solutions or for lip/cheek augmentation. As this second trend requires high injection volumes, it has dramatically fuelled the demand for dermal fillers.


Four technologies of injectables: substituable or complementary?

In addition to traditional promotional campaigns, celebrities and reality TV stars have largely contributed to promoting the use of injectables, particularly among a younger population. But what are the different products on this market and how do they differentiate themselves?

Collagen, the deceased market leader

First dermal filler to be approved by the FDA in 1981, collagen from bovine origin has long been used for regenerating volumes and filling lines in facial aesthetics. Because of Collagen injection site reactions, the lack of antidote and the emergence of more efficient products, collagen has progressively lost momentum. The production of a recombinant collagen at a low cost could reverse that trend but the current state of research is not ready to propose a comeback in the next 10 years.

Botox, the well-established market leader

Botulinum Toxin, commonly called Botox, is produced from the bacteria Clostridium Botulinum. As a neurotoxin, Botox can be considered as a poison for the body due to its potential harmful effects on the nervous system. However, when administered correctly in dermal fillers, it is used to remove wrinkles thanks to its paralyzing function on the targeted muscles. Treatment effect lasts around 4 to 6 months and injection must be repeated to preserve the effects.

Over the past 10 years, Botox has been maintaining its dominant position in facial injections, with a global growth of +5% per year, and globally resisting to competition from other dermal fillers. It is the first non-surgical procedure, representing 59% of all injection procedures performed in 2017.

Hyaluronic Acid (HA), the unstoppable challenger

Hyaluronic Acid is a biopolymer naturally present in the human body (around 15g per human body). HA was originally extracted from rooster combs but is now largely obtained from bacteria bio fermentation. Thanks to its capacity to absorb massive quantity of water, HA can be transformed into a gel with viscoelasticity and moisturising properties (see figure 4). As a natural and friendly compound, HA, contrary to Botox, benefits from a very positive perception from the public.

Depending on the transformation process, HA can be either used as a dermal filler to remove wrinkles (cross-linked HA) or as a skin-booster (linear HA). Treatment effect lasts between 3 months (linear HA) and 12 months (cross linked HA). HA has steadily penetrated the market and is now representing 38% of injection procedures (2017). In Europe, HA is even standing shoulder to shoulder with Botox while in the US, Botox succeeded in preserving its leading position so far.

Figure 4 – Transformation chain of HA (source: Cepton Analysis)

Platelet-Rich Plasma (PRP), the niche competitor

Platelet-Rich Plasma is a concentrate of platelets in plasma free of red blood cells. PRP injections, prepared from the centrifugation of the patient’s own blood to separate the platelets, are used for facial rejuvenation purposes and against hair loss. PRP aims to repair and regenerate the quality of the patient’s skin. The stimulation of growth factors contained in platelets activates the “healing process” of aged tissues and conducts to a “regeneration effect”.

The media coverage, under the name of “Vampire Lift”, largely participates in promoting these therapies. However, considering the time (30 minutes), the expertise and the equipment required to prepare the injectable, barriers remain high to the penetration of PRP over other existing and well-established technologies.

Figure 5 – Injection sites of different technologies of injectables

Although all these technologies are used as stand-alone injectables, most of them coexist and can even be associated. First, PRP plays a different role and does not have the required filling properties to be used for wrinkles removing. PRP and HA can therefore be combined to provide enhanced anti-aging skin properties: HA would provide the volume corrections and PRP the skin rejuvenation. Second, products such as Botox and HA have different injection sites, which makes these technologies complementary.

Clear skies for the medical aesthetics market

As a conclusion, the medical aesthetics industry is a continuously-growing market with very few hurdles, apart from health and sanitary hazards. Dermal fillers being now classified as Class III injectable medical devices in the European regulation, the increase in regulatory requirements is likely to raise new market hurdles for smaller players and to lead to further market consolidation.

It certainly remains one of the most profitable industries with significant margins at each step of the value chain: manufacturers, distributors and physicians. The search for more “natural”, body-friendly, and safer practices being today’s opportunity to capitalize on.



The History of Injectable Facial Fillers, T. Kontis and A. Rivkin, 2009

Global Statistics from the International Society of Aesthetic Plastic Surgery (ISAPS), 2010-2017

Reports on the Emerging Trends in Aesthetic Medicine in 2018, International Association for Physicians in Aesthetic Medicine, 2018

L’IA dans la découverte de médicaments: les robots découvriront-ils les entités moléculaires nouvelles de demain ? (article en anglais)

By Valentin Fleury and Marc-Olivier Bévierre  – CEPTON Strategies


Artificial Intelligence (AI) is taking the old concept of “Rational Drug Design” to a new dimension. The time has not come yet where robots will replace medicinal chemists, but drug discovery in the small molecule area is on the brink of a radical transformation.

The economist Joseph DiMasi (Director of the Tufts Center for the Study of Drug Development) published a study [1] highlighting a multiplication by 6, between 1991 and 2013, of the costs of research and development engaged for a single molecule to reach the market: from ~€450m in 1991 versus ~€2,560m in 2013.

According to Deloitte’s annual report “Measuring the return from pharmaceutical innovation”, the return on investment of the big pharmaceutical companies is steadily decreasing (10% in 2010 versus 3.2% in 2017), thus predicting a possible shift in negative ROI by the beginning of the 2020 decade. This efficiency crisis shakes the traditional model of the pharmaceutical R&D to such an extent that it becomes urgent to adapt it.


The long and expensive way leading to drug discovery…

The research and discovery of small molecules (as opposed to biologics, which are bigger molecules, more complex, and less stable) can be seen as a succession of steps of molecules’ identification and selection. It is usually segmented into four major steps:

Figure 1 – Drug Research and Discovery steps

Lead optimisation remains a puzzle for chemists that compares to the Rubik’s cube: maximise a parameter, you will degrade another one. This step alone concentrates 20% of total research and development costs.

Next steps are more widely known to the general public: in preclinical research, the best molecules are tested on vivo models to assess their toxicity, pharmacology and pharmacokinetics. Finally, one (or more) drug candidate enters the human clinical trial phase. This is the “development” part which usually lasts several years (10 years on average, according to Bernstein Research) and accounts for 60% of total R&D costs.

Why is pharma R&D productivity declining?
The reasons for this decline in productivity are numerous and have been intensively discussed [2]. Among them, two reasons stand out, in our opinion.

First: pharmaceutical R&D addresses more complex pathological processes today than in the past. In other words, we have found medicines for all the ‘easy diseases’, and we are now facing the “difficult” ones.

The second reason is based on a technological bias: the scientific and technical progress of the 80s and 90s allowed the industrialisation of certain research stages. For instance, High Throughput Screening (HTS) or more recently DNA-encoded chemical libraries have artificially inflated the number of leads generated, by increasing the capacity of the filtration stages, without increasing their quality in similar proportion. Thus, more molecules, not better ones, have been pushed through later stages of development, generating more spending without better results in the end.

Thus, the pharmaceutical industry is now seeking to reduce operational costs and improve cycle time within research and development. And AI’s ability to reduce drug development times is increasingly established.

The potential of AI in drug discovery

To improve productivity in small molecule discovery, the key challenge is to find a molecule (the identification part of the process) that maximizes a large number of very diverse criteria, which will be tested sequentially, one after the other (the selection part). Artificial Intelligence (AI) makes it possible to build holistic models for the design of new drugs where these tests can be performed simultaneously, in silico.

The use of deep learning algorithms in drug discovery became widespread in 2012, after Georges Dalh won the Merck Molecular Activity Challenge by demonstrating the effectiveness of little trained deep neural networks to predict the activity of a molecule starting from its structure [3]. This has automated a discipline well known to chemists: QSAR (Quantitative Structure-Activity Relationship).

In 2016, in an article entitled “Automatic chemical design using a data-driven continuous representation of molecules“, Alan Aspuru-Guzik et al.[4] describe a method of continuous and multidimensional representation of the chemical space using deep neural networks. This method allows a simpler, faster and more comprehensive exploration of the chemical space (estimated at 1060 molecules potentially usable as a drug), and ultimately, the generation of virtual molecules previously inaccessible even via the largest databases (containing about 108 molecules).

A case study…

One of our clients, IKTOS, a French start-up founded in 2016, has developed an AI technology capable of generating molecules under the constraint of a set of physicochemical and biological characteristics, according to in silico predictive models of such characteristics.

IKTOS technology is based on the interweaving of three algorithms, which are orchestrated to enable an efficient exploration of the chemical space in an iterative manner and enable the identification of optimal in silico compounds in a few hours of computation.

The first is a generative model: trained on databases containing several million chemical compounds, it can “build” virtual molecules located anywhere in the chemical space (implementing a principle close to that proposed by Gomez-Bombarelli et al.).

The second is a predictive algorithm: trained on a customer database that contains already available and tested molecules, those models can predict the physicochemical and pharmacological properties of a molecule only from its chemical structure.

The third is the reinforcement algorithm: the reinforcement component uses the information (scores) provided by the predicted models on the previous sets of generated molecules to modify the weights of the generative model in order to orientate the molecule generation in the right direction.

This technology has demonstrated[5] its effectiveness through a collaboration with a major pharmaceutical company. For 10 years, the chemist team had tried to make compounds maximising a set of 11 biological activity criteria. Among the 900 compounds that they had synthesized and tested; they were not able to find any molecule hitting more than 9/11 success criteria. In just a few days, IKTOS technology generated 150 virtual molecules which were predicted to meet all 11 criteria, in silico. Out of those 150 molecules, 11 were selected (based on their synthetic accessibility and originality), synthesized by the chemists, and tested on all 11 criteria. 9 molecules were found to maximize 9 criteria, 3 to maximize ten criteria, and 1 molecule was found to be good on all 11 success criteria. It took only a few days for an AI, and 11 molecules, to achieve better results than what had been achieved by a team of chemist experts over 10 years of benchtop research and 900 trials of molecules.

An emerging field attracting massive investments

The use of artificial intelligence in small molecule research is quite new, and it is still difficult to figure out how far it will go. We have identified -and often met as well- more than a hundred companies (mainly start-ups) at the crossroad of pharmaceutical R&D and AI. Many start-ups are flaunting attractive technologies, but those who are really able to deliver high value-added and actionable results are still few in number. In addition, the still limited number of success stories and the confidentiality that surrounds most of them contribute to a lack of clarity among medicinal chemists around the applications of AI in their profession. In fact, big pharma is still seeking to understand the possible applications of AI, and to evaluate existing technologies and stakeholders.

Numerous partnerships have been signed recently, demonstrating the growing interest in the area (Sanofi with Exscientia and Recursion, Merck with Atomwise, GSK with Cloud pharmaceuticals, InSilico Medicine and Exscientia, Iktos and Janssen, Iktos and Merck). The increasing number of scientific publications in recent years also reflects the enthusiasm of the scientific community and the industry. In addition, private investments are accelerating (~$30m invested in 2012 versus ~$500m and ~$800m in 2014 and 2016 respectively). The enthusiasm of investors is all the greater when certain start-ups, initially service providers of R&D for the pharmaceutical industry, develop their own pipeline of molecules and thus compete frontally with traditional biotech startups. Benevolent AI, whose first clinical trials on Parkinson’s disease began in 2018, holds 20 molecules in the preclinical phase, and has recently raised $115m. Today, it is valued at $2bn.

Towards automated drug discovery?

Certain companies (like SRI or Catapult Medicine Discovery) aim at developing a fully automated research workflow, from automated design and retrosynthesis to robotised synthesis and tests. We are not among the few utopians who believe in the total automation of pharmaceutical drug discovery. Nevertheless, AI will certainly contribute to deeply transforming pharmaceutical research. As some say, “AI will not replace medicinal chemists, but medicinal chemists who use AI will replace those who don’t”. Investments of pharmaceutical companies in AI are nibbling budgets of benchtop research and computational chemistry, progressively driving research activities to more in silico and automated methods. Today, most of the major names in the industry develop partnerships with companies mastering these technologies. The question remains whether they will try to internalise it or not. If not, we expect to see in the next few years the emergence of a new model of AI-based biotech start-ups, with highly automated discovery processes, and sufficient funding to develop their own pipeline.


[1] DiMasi JA, Grabowski HG, Hansen RA. “Innovation in the pharmaceutical industry: new estimates of R&D costs”. Journal of Health Economics 2016
[2] J.W. Scannel et al. “Diagnosing the decline in pharmaceutical R&D efficiency”. Nature 2012
[3] George E. Dahl et al. “Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships”. Journal of Chemical Information and Modeling 2015
[4] Alan Aspuru-Guzik et al. « Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules”. ACS Central Science 2018
[5] “Deep Learning For Ligand-Based De Novo Design In Lead Optimization: A Real Life Case Study”. Iktos and Servier Poster 2018

CEPTON parmi les cabinets de conseil incontournables en Santé et Industrie Pharma selon le magazine “Les Décideurs”

Pour la deuxième année consécutive, l’étude publiée par le magazine “Les Décideurs” classe CEPTON parmi les meilleurs cabinets de conseil en Santé et Industrie Pharmaceutique (2018). Douze ans après la création du cabinet, c’est une formidable reconnaissance pour le travail et les efforts de notre équipe.

Décideurs 2018 ranking

Lien :