Eric Luellen, Biotechnology

Hi, I'm Eric Luellen, an executive & strategist in data science & AI innovation in pharma, medical devices & biotechnology industries -- 3x founder -- xCTIO, CTO, CDS & CEO

Eric Luellen's Bio:

Eric Luellen leads the cultivation of new ideas, inventions, strategies, and technologies in applied data science, AI/ML drug discovery, research & development, and technologies such as digital health companion apps and software & machine learning as a medical device. His passion is dedicating energy, training, and time to meaningful and purposeful research and biomedical and digital health applications that focus on and benefit children. For 27 years, Eric Luellen has led teams, divisions, and organizations to develop custom analytical and data science solution technologies while serving as a Chief Technology & Innovation Officer, Chief Data Scientist, Chief Technology Officer & Chief Executive Officer. Eric Luellen has broad biomedical domain subject-matter expertise in biostatistics, epidemiology, genomics, digital theragnostics, drug discovery, and SaMD. Eric Luellen has founded three companies, exited two and scaled one. He has led teams up to 140 people and budgets of up to $10 million. Eric Luellen holds a Master of Public Health (MPH) degree concentrating in practice management and biostatistics from the University of Massachusetts Amherst, a Master of Science (MSc) in medical informatics from Northwestern University, plus 37 credit hours in biomedical sciences from Harvard University. Eric Luellen also holds 10 advanced certificates in business, finance, management, negotiations, and technology from Caltech, Columbia Business School, Harvard Law School, the Sloan School of Management at MIT, and the Wharton School of Business at the University of Pennsylvania, where he also completed a fellowship in e-commerce.

Eric Luellen's Experience:

Chief Technology & Innovation Officer at Stealth Mode Biotech
January 2023 - Present | Boston, MA
Leading AI drug discovery and development of AI-powered biological discovery platform (i.e. computational gain & loss of function) applied to integrated multi-omics to discover disruptive theragnostics. Focused on rare pediatric diseases. * Led the discovery of 19 multi-omic diagnostics or treatments; * Led the filing of 23 provisional US patents * Lead external AI drug discovery via multiple research agreements * Lead regulatory interactions for approvals
Chief Technology & Innovation Officer at Infinant Health, Inc.
May 2022 - December 2022 | Norwalk, CT & Davis, CA
A Gates Ventures & J&J-backed Series D microbiome startup. Led a team of PhDs and contractors with multi-million budget responsible for six areas: (1) drug discovery (wet & dry labs); (2) regulated & companion diagnostic apps (SaMD & MLaMD); (3) data mining indication expansions; (4) developing a "data-as-an-asset" strategy; (5) strategic relationships (trials, partnerships, M&A identification); and, (6) innovating ideas that defined the company's future (access, trial strategies, etc.). * Led identification of indication expansions featured in Hot Topics in Neonatology affecting 1K babies & saving integrated provider $52 million per year, indications to reduce TPN (14%), antibiotics use (40%), and sepsis (73%) in NICUs. * Ideated and led the SDLC (discovery, design & development) of three BETA regulated apps (SaMD/MLaMD) to predict colitis, dysbiosis, and cognitive delays and oversaw the development of a QMS library for SaMD certification in 3 months, 100-300% faster than typical. * Company down-scaled all executives and changed strategies, now single-asset VC run.
Head of Software as a Medical Device (SaMD) at ConvaTec plc
July 2021 - April 2022 | Greater Boston
Inaugural lead of conception, strategy, and execution of new product development division -- software as a medical device (SaMD) and machine learning as a medical device (MLaMD) -- for $2B publicly traded global medical device company, focused on 12 next-generation technologies and necessary capabilities.
Co-founder, CEO & Chief Data Scientist at Bioinformatix.io
August 2015 - June 2021 | Boston, Massachusetts
Led team of 7 to invent, design, and develop a next-generation AI platform and provide biomedical data science commercial development organization (CDO) services. ● Led discovery of leading candidate for broad-based COVID 19 attenuated virus vaccine published in BioRxiv with Top 1% Altmetric score using novel machine learning and genomic targeting techniques ● Led discovery of the pathogen-immune relationship of SARS-CoV-2 & model to predict immunity, published in JMIR with Top 5% Altmetric score ● Led development of MLaMD autonomous real-time bio-surveillance disease intelligence engine prototype for zoonoses with pandemic potential at the time of sequencing and posting to global biobanks briefed to US national security community ● Led development of digital therapeutic for arthritis and inflammation for US Air Force Research Laboratory with 80.6% accuracy ● Led design & development of AI platform to optimize medication adherence, care coordination & pharmacovigilance that won two global innovation contests: Startupbootcamp & Tencent Cloud AI; and finalist in three innovation competitions -- C3 Prize @ Stanford MedX, World Technology Award in health & medicine, and SLUSH Shanghai
Chief Data Scientist at Love Justice International (part-time evenings)
November 2019 - June 2020
Led data science strategies and implementation across projects for a global charity focused on combatting human trafficking, family homes and schools for orphans, and COVID-19 relief efforts across 14 countries (part-time after hours). Representative projects included: ● Talent ID - Developed an algorithm to predict the highest performers with 77-97% accuracy using best subset multiple regression ● Nutrition - Developed analysis to identify and plot malnourished children by percentage BMI. ● Trafficking Prevalence - Co-developed research study to measure the prevalence of human trafficking. ● Trafficking Prediction - Developed an algorithm to predict whether or not a person was being trafficked using a comparative ensemble of decision trees, random forest, extreme gradient boosting, logistic regression, and neural networks in R. ● Trafficking Locations - Developed an algorithm to predict which borders had the highest prevalence of trafficking to prioritize border monitoring using Poisson and stepwise regression or ordinal data. ● Fundraising - Developed algorithms to segment donors by behavior using self-organizing maps and predict attrition using random forests and extreme gradient boosting in R.

Eric Luellen's Education:

UMASSS-Amherst
2018 – 2020
Master of Public Health (MPH)
Concentration: Practice Management & Biostatistics
Activities: GPA 3.9
Northwestern University
2016 – 2017
Master of Science
Concentration: Health Informatics & Technology Applications
Activities: GPA 3.8
Harvard University
2006 – 2015
Graduate studies (36 credit hours)
Concentration: Medical genomics, virology and immunology, infectious disease, neurobiology, epidemiology
Activities: GPA 3.3
Harvard University
2006 – 2008
General Studies
Concentration: Neurobiology, epidemiology, infectious disease & environmental sciences
Harvard Law School
2001 – 2001
Certificates (5)
Concentration: Program on Negotiation
Activities: Dealing With Difficult People & Difficult Situations (June 2001) The Program on Negotiation for Senior Executives (April 2001) Dealing with an Angry Public (May 2001) Managing the Difficult Business Conversation (April 2001) Negotiating Labor Agreements (July 2001)
University of Pennsylvania's Wharton School of Business
2000 – 2001
Fellow
Concentration: E-commerce
California Institute of Technology (Caltech)
2000 – 2000
Advanced certificate
Concentration: Business process re-engineering
Massachusetts Institute of Technology (MIT), Sloan School of Management
2000 – 2000
Advanced certificates (2)
Concentration: Finance & technology
Columbia University, Graduate School of Business
2000 – 2000
Advanced certificate
Concentration: Mergers & acquisitions
CalTech
2000 – 2000
Advanced Certificate
Concentration: Business Process Re-engineering
American University
1990 – 1995
Bachelor of arts
Concentration: Liberal Arts & Economics

Eric Luellen's Interests & Activities:

Eric Luellen was a global finalist for the 2016 C3 Prize at Stanford MedX, World Technology Prize for health & medicine, 2017 American winner of Startupbootcamp Digital Health Accelerator in China, and honoree in the Tencent Cloud AI Startup Pitch Competition. He is the author of "Beating Amazon," a machine-learning textbook and has a readership of over 100K in Towards Data Science. His peer-reviewed published research has twice ranked in the top 5% by Altmetric scores. Eric Luellen is an emeritus officer of the Young Presidents Organization (YPO) and Society for Information Management (SIM).

Eric Luellen

Biotechnology Executive (AI, ML, SaMD, R&D) | Biotechnology

Hi, I'm Eric Luellen, an executive & strategist in data science & AI innovation in pharma, medical devices & biotechnology industries -- 3x founder -- xCTIO, CTO, CDS & CEO

Eric Luellen's Bio:

Eric Luellen's Experience:

Chief Technology & Innovation Officer at Stealth Mode Biotech

Chief Technology & Innovation Officer at Infinant Health, Inc.

Head of Software as a Medical Device (SaMD) at ConvaTec plc

Co-founder, CEO & Chief Data Scientist at Bioinformatix.io

Chief Data Scientist at Love Justice International (part-time evenings)

Eric Luellen's Education:

UMASSS-Amherst

Northwestern University

Harvard University

Harvard University

Harvard Law School

University of Pennsylvania's Wharton School of Business

California Institute of Technology (Caltech)

Massachusetts Institute of Technology (MIT), Sloan School of Management

Columbia University, Graduate School of Business

CalTech

American University

Eric Luellen's Interests & Activities: