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STRATEGIC ROADMAP - 3 YEARS
STRATEGIC ROADMAP - 3 YEARS

2020 - 2023 STRATEGIC PLAN

The strategic planning process is a series of outcomes that build upon each other to ultimately transform our organization to reach our desired future state.

Achieving these outcomes requires everyone in our organization to be heading in the same direction with a shared vision.

Our plan is organized by four areas of strategic focus:

Current State

Strategic Direction

Roadmap

Delivering Results

Each section is a fundamental building block of our plan.

CURRENT STATE: SUMMARY & SWOT

Taking time to reflect on your organization’s current state by conducting a SWOT exercise is a primary foundational element in building a strategic plan. It often clarifies key considerations, which need to be carried forward into the planning process, including strategic priorities and core areas of focus.

In Silico modelling platform : data extraction and aggregation models = 20%, deep learning pipeline under early development.

Software application: visual reactive prototype = 20%, backend system =5%, frontend under early development.

Biological disease models platform: cells and organoids characteristics and specific needs/improvements over existing models is being evaluated through end-users interviews. Development starting in the coming months in partnership with two academic partners the Institute for Regenerative Medicine and Biotherapy and the organ-on-chips lab at Institut Pasteur.

SWOT ANALYSIS

Strength:

Extensive knowledge of similar product and long experience selling it

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High profile & large network in go-to-market : senescence research community

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Each founder has combined expertise in biology, deep learning, business management

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Competitive advantages from rare integrated approach (biology & deep-learning): massive quality datasets, access/self-reliance, high predictive power

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Weaknesses:

Consequent biology & algorithm technology development needed

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Relatively long time horizon before revenues

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Long and specific process for clinical POC

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Opportunities:

Can expand predictive platform at scale through academic offerings

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Demand for in vitro/in silico solutions is high and growing : expand services to biopharma market for pre-clinical research

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Highly sought after solutions in the clinical spaces :

expand offerings in clinical trials and personalized medicine

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Potential to develop in-house therapies on the long term: Market alternative approach / Pharma disruption

Threats:

Pool of qualified potential new hires reduced due to combined expertise needed

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Increasing interest in deep learning approaches from big pharma companies and new entrants

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Potential push back from users of traditional approaches

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OUR STRATEGIC DIRECTION: MISSION, VISION & VALUES

Mission Statement: Why do we exist? What is our core purpose?

Our mission is to accelerate the discovery of novel treatments by providing highly predictive models of biology.

Vision Statement: Where are we going

We aim to radically transform humanity’s ability to understand and impact biology by creating the first fully predictive biological models.

° For our partner community this means : offering high fidelity models of biology to radically accelerate fondamental, pre-clinical and clinical research.

° For our team this means : being the most knowledgeable team of experts about predictive biology (in vitro and in sitro integration).

Competitive Advantages: How will we win?

Creating the conditions for scale

° Provide a very high-user-experience on a single application, integrating in vitro and in silico analytics

° Build better, predictive disease models integrated on the appliction :

Highly representative stem cell derived organoids, improving on current limitations

Advanced deep learning pipeline derived in silico models

° Lower the cost and ease of use of predictive models

° Offer seamless solutions for collaborative research & federated learning

° Monitor user needs and always improve market fit

Scaling : academic adopters and research collaborations

° Provide solution to academic users at scale based on existing network and BD strategy

° Develop and generate deals from a strong network of privileged relationships with Pharmas, Hospitals & Patient associations (from founding team, BD, hirings)

Building a superior offering: technology excellence

° Leverage unmatched generation of high-quality experimental data from scale

° Develop superior technology : use high quality data and technological expertise to build the most predictive biology platform, constantly improving in silico models ( automatised contrasting of prediction with real outcomes)

Building a solid revenue generation pipeline : operational excellence

Predictive POCs and Sales engine

° Develop a predictive proofs of concept engine :

Leverage network and experience in selling similar solutions : complex POCs, regulations and HEOR specificities

Operational efficiency : formalize and automatise parts of the process to scale the generation of preclinical and clinical POCs

° Develop a solid BD and sales pipeline :

Leverage network and experience in selling similar solutions : complex POCs, regulations and HEOR specificities

Operational efficiency : formalize and automatise parts of the process to scale the generation of preclinical and clinical POCs

° Develop offering based on integrated end to end solution, from fundamental to pre-clinical and clinical research : allowing for opportunistic cross-sell and up-sell and raising switching costs.

Team expertise

° Build a team with hard to beat, growing expertise in predictive biology, at the intersection of life sciences and deep learning

° Maintain and develop superior knowledge of the complex POCs, regulations, HEOR specificities.

processes and milestones involved in selling predictive solutions in preclinical and clinical contexts in our target markets.

BUSINESS MODEL

Our business model is based on 4 revenue streams:

Software application subscription fees/SaaS model

Technology Platform access fees/Predictive biology services

Shared IP and Licensing fees through R&D partnerships - Mid-Long-Term

Developing in-house therapies - Long Term

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Defensibility & Assets creation

01 Bio-engineering

We create complex engineered cells and tissues for a variety of applications, from academic research to clinical trials : a highly defensible product in terms of expertise and IP protection.

02 Software, AI and Bio-informatics

Our software and deep learning platform are built on in-house research and development: it leverages combined expertise in Informatics, Biology, Insilico modeling, Deep Learning, and Graph Analytics with the objective of pushing the boundaries of what can be achieved. Our tech stack and codebase is not made publically available and provides high technology defensibility.

03 Legal & Regulatory

The pharmaceutical and clinical environments are highly regulated complex environments, providing innovative approaches in such environments necessitates high levels of expertise and knowledge, we have specific expertise in-house and have strategic goals planned around the expansion of this expertise. The proofs of concepts needed are also developed over time with considerable business development, networking, regulatory and scientific efforts. These elements combined provide high hurdles to potential entrants.

04 Ecosystem

We direct our efforts towards the development of an ecosystem business model. Part of that work is used to building a large network of academic and corporate partners . The platform itself is designed to benefit from economies of scale and sustain multiple research projects concurrently.

TEAM

Jimmy Le Vagueresse

Jimmy worked on both scientific and commercial aspects of the Pharmaceutical Industry. He is a former member of the Market Access department at Bristol Myers Squibb and a former Life Science Strategy consultant.

He carried out strategic consulting, pharmaceutical pipeline management and market access missions with several of the world's largest pharmaceutical companies, including Sanofi, BMS, Pfizer and Lundbeck.

He graduated in Neurobiology (BSc) and in Therapeutic Bio-engineering (MSc) and worked on research projects at the CNRS, UK’s National Institute for Medical Research and College de France.

He holds degrees from the London Business School (PhD 2 years - MSc), ESSEC (MBA), KEIO University (MBA), and is a former member of the Sanofi Chair in Therapeutic Innovation.

He studied and applied Graph theory (at UCL) and Agent-Based Simulations (at LBS) in research contexts and applies deep unsupervised learning methods to biology.

Anthony Lagnado, PhD

Anthony is a cellular and molecular biologist with an expertise in Stem Cells and Senescence.

He contributed significantly to the understanding of the role of mitochondria and telomeres dysfunction during cell senescence. He worked in several world-renowned institutions, including research in induced pluripotent Stem Cells at the Institute of Regenerative Medicine, with, skin tissue at Newcastle University and on aging biological processes with Dr. Passos, a pioneer in aging-related diseases at the Mayo Clinic. Among other contributions, he is involved in the development of unique methodologies for analyzing telomeres dysfunction using super-resolution microscopy and reporter systems that allow us to see the dynamics of telomeres damage in living cells. He develops deep learning computer vision methods applied to microscopy.

He holds a Marie Curie PhD in Biology, a Post-Doctorate in Cellular Senescence and a Master in Bioedical Engineering.

Johan Estellon PhD

Johan is an expert in genomics and bioinformatics, with proven track records of delivering and sustaining revenue and profit gains within highly mutating markets.

He is a senior commercial executive with a long experience applying commercial and scientific skills to the marketing and business development of several biotech companies, including Cephalon, APCure, Genostar and Congenica.

He worked on genomics business development for 11+ years, with a focus on Personalized Medicine, Bioremediation and Diagnostics markets and technologies.

He holds a PhD in Bioinformatics, MSc in therapeuthic bio-engineering and Business Management Msc.