West Sweden Artificial Intelligence An Inspirational Map

Transcription

1 West Sweden Artificial Intelligence An Inspirational Map

2 West Sweden Artificial Intelligence An Inspiration Introduction Åsa Lindström, Sahlgrenska Science Park Erik Behm, Business Region Göteborg Inspirational Map of Big Data, Machine Learning & AI Johan Hogsved, haw & co Inspirational Map of AI in Life Science Petra Apell, Aproficio AB The Map Selected Industries, Companies & Actors Next Steps

3 West Sweden Inspirational Map of Big Data, Machine Learning & AI

4 Disclosures Petra Apell 26 years of experience from Pharma, MedTech & BioTech. M.Sc Chemistry, Gothenburg University. PhD student, Chalmers University of Technology. Serial entrepreneur. Current ventures: 10MD and Aproficio. AI experience is somewhat limited. Extensive experience from applying new technologies, e.g. ehealth and Virtual Reality, in medical applications. Working as a consultant for Sahlgrenska Science Park. Disclosures Johan Hogsved 20 years of experience in combining Tech, Business & Leadership. M.Sc. Engineering Physics, B.Sc. Business Administration. I run a company in IT-development & management consulting and a startup in robotic automation. Working as a consultant for Business Region Göteborg.

5 The Mission Create an map featuring West Sweden actors in the Big Data, Machine Learning & AI arena Is it possible to find 100 companies and organisations in the Gothenburg Area only?

6 Definitions used here Big Data: The use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data. Machine Learning: A field of computer science that gives computers the ability to learn without being explicitly programmed. Artificial Intelligence: When a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving.

7 What we laughed at in 2014

8 Where we are today

9 Partners Applications (verticals) BIG DATA, MACHINE LEARNING & AI INSPIRATIONAL MAP WEST SWEDEN 2018 Transport & Automotive Internet & Security Financial & ERP Life Science Other verticals Service Research & Education Incubators & Arenas

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11 Volvo Cars - Innovation in Transportation

12 Volvo Trucks - Innovation in Transportation

13 AI LANDSCAPE TRANSPORT & AUTOMOTIVE For Volvo Cars, technology should make people s lives easier. That s why our approach to autonomous driving is all about the people that will use them. Our future cars will be able to navigate without human input, equipped with sensors that read the surroundings, adapting to changing traffic conditions. Our work is about where the technology meets the customer benefit. As a starting point, we look at the demands put on customers by their customers. We are focused on solutions that can make difficult, repetitive and timeconsuming tasks easier for all concerned. Hayder Wokil Autonomous & Automated Driving Director, Volvo Truck Our company originates from the safety leaders of the automotive industry. We are young as a company but our starting point builds on robust industrial automotive solutions. We have a unique skillset from Tier 1 and OEM domain knowledge. All the way from sensors to vehicle control. We have joined forces to create an independent company offering our passion, technology, and solutions. Veoneer s ambition is to be a leading system supplier for ADAS and autonomous driving as well as a market leader in automotive safety electronics products. Veoneer has the world s broadest automotive safety product portfolio, comprised of state-ofthe-art active safety systems, restraint control systems, and brake systems.

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15 Recorded Future - Innovation in Cyber Security

16 AI LANDSCAPE INTERNET & SECURITY You need more than just internal network data to uncover evolving and stealthy threats. We believe machine learning combined with human expertise is unrivaled at scaling the delivery of contextualized threat intelligence. The world s premier platform for accumulating knowledge and building intelligence A revolutionary, open and modular digital investigation software used by national security, defense and law enforcement agencies around the world. Halon consists of a dedicated team of doers. Together we have set out to change the landscape of technology, by enabling service providers to tailor their perfect infrastructure. To err is human, they say. But in the security business, the goal is a zero fail rate, something nobody comes closer to than Irisity. Irisity s solution: To combine Artificial Intelligence and Machine Learning and couple it with vigilant human input.

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18 AI is getting ready for healthcare. But is healthcare ready for AI?

19 Traditional life science players are active in digitization Our newly appointed Chief Digital Officer will help us transform our business model using digital technologies. To improve the way we use data in drug discovery and development, engage with patients, doctors and other stakeholders. And automate our business processes. Jim Jimenez, CEO Novartis GSK has consistently been active in the digital space, most recently looking to apply AI to drug discovery and medical device mobile apps. The impact of technology on the healthcare industry is accelerating and requires us to rethink our approach. Emma Walmsley, CEO GSK Through advanced tools like machine learning, we can understand which individualized therapies will be the most effective for improving quality of life, reducing healthcare costs, and preventing relapse and remission in specific segments of the population all the way down to individualized care. Stuart McGuigan, CIO, J&J

20 AI can create value across the value chain R&D - Drug discovery - Drug Design - Clinical trials Product & service - Supply & distribution - Product portfolio - Education User experience - Diagnosis - Patient support - Decision support

21 Approach to analyzing AI adoption levels in West Sweden Main purpose Identify companies that address AI opportunities or apply AI technologies. Secondary purpose Catalyse the continued development of AI related life science projects. Methods Sources: www, innovation system, funding agencies, EU applications, network, virtual communities, public reports, newspapers, etc. Interviews: 10 senior developers and managers. Adoption level: 1 = Corporate strategy to address AI opportunities. 3 = Partial AI adopters or experimenters. 5 = AI adopters with proactive strategy and implemented solutions.

22 Life Science NOTE: List may not be complete, new companies are continuously added. List contains companies engaged on different levels.

23 AI used in a variety of applications across the value chain 11% 11% 38% 16% 11% Drug discovery & design Product / service Diagnostics Education Decision support Patient support 13%

24 AI adoption level per application 100% 80% 60% 5 AI adopters with proactive strategy and implemented solutions 3 Partial AI adopters or experimenters 40% 20% 1 Corporate strategy to address AI opportunities 0% Drug discovery & design Product / service Diagnostics Education Decision support Patient support

25 Identified challenges Start-ups who might have the technology, might not have access to data. Which data sets are the most important ones? Structure and annotate data. Ownership of data - patient or company? Complexity is a limiting factor Sometimes difficult to show return on investment (ROI). Regulatory clash between the dynamic and the traditional approach.

26 Integrative Research Laboratories Peder Svensson, Dir Comp Chem & Biol, CIO

27 Drug discovery the dominating picture Human pathophysiology Animal models In silico drug design. Virtual HTS Ex vivo models Big Data & AI Cell-based assays Binding assays High throughput screening (HTS)

28 ISP - a useful complement in drug discovery Human pathophysiology Computational modelling at all stages, including AI methods Animal models In silico drug design Ex vivo models Cell-based assays Starting point Binding assays

29 Computational modelling including AI methods Support for idea generation, Quantitative Structure-Activity Relationships (QSAR) Design of experiments / compound selection Visualization and interpretationof data Systems pharmacological translational modelling using physiologically relevant, uniform and comparable data of high quality

30 Artificial arms get closer to the real thing Integrum has developed new breakthrough technology to connect bionic prostheses to the patient s bone, nerves, and muscles. Robotic prostheses controlled via implanted neuromuscular interfaces have become a clinical reality thanks to Integrum s osseointegrated technology. Founders: Per-Ingvar Brånemark & Richard Brånemark We have used osseointegration to create a long-term stable fusion between man and machine Max Ortiz Catalan, Chalmers University of Technology.

31 INCREASE VALUE AND LIMIT RISK IN R&D PROJECTS AND PORTFOLIOS

32 STRATEGIC QUESTIONS & UNCERTAINTIES IN R&D PROJECT PORTFOLIO Development Launch Market Targeted paitents? How to develop? Cost vs Speed? Market size & uptake? Competition? Pricing? Invest? What option? Prioritized projects? Incoming project flow? 2% chance of launch 1 busd to reach launch Price pressure Tougher requirements $ Multi busd R&D spending ROI less than 5%

33 EVALUATE AND COMPARE OPTIONS ITERATIVELY TO MAXIMIZE VALUE AND LIMIT RISK Quantitative evaluation of value & risk New insights & new ideas Project/portfolio simulations Design of options & scenarios Captures all knowledge incl. all complexities and uncertainties Risk optimized against the financial outcome Easy to compare options Potential areas of improvement are highlighted Game-like and dynamic

34 Captario enables decision-making for drug development projects in a way I have not seen it before. It sets a new benchmark to assess the complexity and uncertainty of pharmaceutical portfolios to identify and address upcoming opportunities and gaps in the pipeline. Daniel Daetwyler Head Portfolio Management & Global Decision Support

35 Key findings life science There are extensive digitization activities and rapid growth across all fields in life science in the region. There are increased understanding of opportunities relating to AI applications in life science and healthcare. There is potential for increased collaborations between companies, regional Academic centers and Healthcare providers.

36 In the mind of AI savvy individuals I wish more AI developers would choose to work with life science it s definitely a growing field! The buzz around AI has resulted in an increased understanding of the capabilities of AI within our management team. That is very helpful. If we can improve compound selection early in the drug discovery phase with the help of AI, we will definitely cut costs! It is superexciting to work across the fields of medicine, technology and economy to solve the challenges healthcare face today. I don t think that clinicians will be replaced by AI solutions. What we can do is to equip Doctors with intelligent tools so they can make even better decisions.

37 Change is inevitable. Progress is optional.

38 Key Findings Rapid growth in the region Found in almost every vertical Usage of technologies adapted to need The possibilities using the technology increases and the threshold to start gets lower and lower All actors are not world leading in AI but use it to improve their current business Life Science Internet & Secuity Transport & Automotive Partners Incubators & Arenas Research & Education Financial Internet & ERP

39 CONFERENCES & MEETING SPACES SPREADING THE WORD Metis Forum Pre-Hospital ICT Arena GAIA Machine Learning & Data Science Conference Vehicle Electronics & Connected Services Lindholmen Foss North Vitalis E-health MedTech West Workshop Invitation only Gothenburg Tech Week ISCE 2018 International Conference on Software Engineering Lindholmen Software Development Day Park Annual 2018 Life Science, incl. Digital Health & MedTech MeetUp Machine Learning & Data Science (GBG)

40 Thank you!