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AI in Drug Discovery USA
21 October - 22 October 2024
AI in Drug Discovery USA

 Artificial Intelligence (AI) has taken the lead in technological advancement across the pharmaceutical sector. It is expected to transform pre-clinical drug discovery through reducing costs by up to 40% and creating a market worth up to $50 billion in the next decade.

Are you ready for this transformative period?

Hear first-hand the latest AI advancements across the pharmaceutical sector directly from experts in the field and obtain strategies to support your operations at the highly anticipated AI in Drug Discovery conference.

Driven by a move towards personalised therapies and novel drug candidates, Artificial Intelligence (AI) has taken the lead in technological advancement across the pharmaceutical sector. Increased efficiency of the drug discovery process, through innovations including automation, in-silico modelling, and machine learning, accelerate growth in an ever-expanding field, focused on revolutionising modern healthcare.

 

FEATURED SPEAKERS

Dr Bino John

Dr Bino John

Director, Computational Biology, Cancer Immunology and Immune Modulation, Boehringer Ingelheim
Dr Dmitriy Podolskiy

Dr Dmitriy Podolskiy

Associate Director, Astellas Pharma
Dr Petrina Kamya

Dr Petrina Kamya

President, Insilico Medicine Canada Inc., and Global Head of AI Platforms, VP, Insilico Medicine
Dr Stephen MacKinnon

Dr Stephen MacKinnon

VP of Digital Chemistry, Recursion Pharmaceuticals
Dr Vishnu Sresht

Dr Vishnu Sresht

Director, Precision Labs, Genentech

Dr Bino John

Director, Computational Biology, Cancer Immunology and Immune Modulation, Boehringer Ingelheim
Dr Bino John

Dr Dmitriy Podolskiy

Associate Director, Astellas Pharma
Dr Dmitriy Podolskiy

Dr. Podolskiy has previously worked at MIT and Harvard Medical School as Research Scientist on computational systems biology of canrcinogenesis and aging . He currently leads the Bioinformatics team at Astellas Institute for Regenerative Medicine and the cross-divisional AI drug discovery team at Astellas Inc

Dr Fred Manby

Co-Founder and CTO, Iambic Therapeutics
Dr Fred Manby

Dr Joel Karpiak

Head of Protein Design & Informatics, GSK
Dr Joel Karpiak

Dr Kinga Bercsenyi

SVP of Business Development, Arctoris
Dr Kinga Bercsenyi

Kinga Bercsenyi, PhD is the Senior Vice President of Business Development of Arctoris, a tech-enabled CRO based in Oxford.

Kinga completed her PhD at Cancer Research UK, followed by a Sir Henry Wellcome postdoctoral fellowship at King’s College London. She has extensive research experience spanning from early, through preclinical drug discovery, all the way to clinical trials. In her role at Arctoris, she is working tirelessly to support biotech and pharma clients in getting better data, which leads to better decisions and ultimately, better drugs for patients.

Dr Martin Akerman

CTO & Co-Founder, Envisagenics
Dr Martin Akerman

Dr. Martin Akerman is the CTO and Co-founder of Envisagenics. He is the inventor of SpliceCore®, Envisagenics’ flagship platform born of his vision of applying machine learning to RNA information and discovering new drug targets in areas of unmet need.

Martin trained as a postdoctoral fellow with Dr. Adrian Krainer at Cold Spring Harbor Laboratory, where he helped in the development of Spinraza®, the first FDA-approved RNA therapeutic for treating Spinal Muscular Atrophy. Dr. Akerman received his PhD in Bioinformatics from Technion, Israel Institute of Technology, where he studied how RNA splicing can boost functionality of the human genome and trigger diseases.

Dr Petrina Kamya

President, Insilico Medicine Canada Inc., and Global Head of AI Platforms, VP, Insilico Medicine
Dr Petrina Kamya

Petrina Kamya, PhD, is the Global Head of AI Platforms and President of Insilico Medicine Canada, overseeing Insilico’s end-to-end generative AI-driven drug discovery platform, Pharma. AI.


Before joining Insilico, Dr. Kamya had a career in Market Access and held several positions at a software company that developed CADD tools for drug discovery and development.


She holds a Ph.D. in theoretical chemistry and a BS in biochemistry from Concordia University.
 

Dr Rabia Khan

Founder & CEO, Serna.bio
Dr Rabia Khan

Rabia Khan, PhD, MBA is the founder and CEO of Serna Bio, a biotech building the world's first map of the druggable transcriptome to address novel inaccessible biology. The company is using their ML-enabled discovery engine to progress programs in Oncology and Rare disease.
Dr. Khan is a member of the Board of Trustees for the UK Dementia Research Institute, an advisor to No Label Ventures, a fund investing in immigrant founders in the UK and EU and to The First Thirty VC fund. She has also held advisory roles for Creative Destruction Labs.
Dr. Khan has more than 10 years experience building scientific teams and delivering commercial deals at the intersection of machine learning, biology and drug discovery. She was Managing Director, Discovery Sciences at Sensyne Health Plc (now - Arctorus Data) establishing the scientific strategy, building the machine learning and clinical teams by recruiting and leading a team of over 50 machine learning and clinical researchers, and delivering on several significant pharma partnerships including Bayer, BMS, Roche and Alexion.
Dr. Khan has also held senior roles at BenevolentAI and Meta (acquired by Chan Zuckerberg BioHub). At Meta, she was pivotal in the partnership with the Intelligence Advanced Research Projects Activity (IARPA) to acquire horizon-scanning technology that used NLP to research the biomedical corpus. At BenevolentAI, she helped shape the discovery strategy for several programs, led the Age-Related Macular Degeneration and Glioblastoma drug discovery programmes and served as the interface between the technical and biological teams.
Born and raised in Pakistan, Dr. Khan is passionate about supporting diversity in technology and initiatives focused on improving access to care and availability of medicine.

Dr Stephen MacKinnon

VP of Digital Chemistry, Recursion Pharmaceuticals
Dr Stephen MacKinnon

Stephen MacKinnon completed his PhD in Biochemistry at the University of Toronto, with research emphasis on structural bioinformatics.

Stephen led the research and development of predictive technologies for Cyclica, a Toronto-based startup, until their acquisition by Recursion in May 2023.

Stephen is currently VP of Digital Chemistry at Recursion, leading the continuous development and application of machine learning for drug discovery.

Dr Vishnu Sresht

Director, Precision Labs, Genentech
Dr Vishnu Sresht

After a PhD in computational chemistry at MIT, Vishnu worked on developing computational chemistry and machine learning methods for small molecule discovery and development at Pfizer before joining Genentech.

He currently leads a group developing methods to integrate machine learning methods alongside physics-based and cheminformatic approaches into target validation, hit discovery, and the DMTA cycle for small molecule discovery.

Raya Stoyanova

Data Scientist, MLOps, Roche
Raya Stoyanova

I have a background in machine learning and data science within the pharmaceutical industry, with extensive experience across various domains, primarily focusing on small molecules. Recently, I transitioned into the MLOps domain at Roche, where I am concentrating on developing a robust platform that enables data scientists to onboard their models as efficiently as possible. My work involves streamlining the deployment process and ensuring scalability. This platform aims to enhance the accessibility and operationalization of machine learning models, ultimately driving innovation and efficiency in pharmaceutical research and development.

Senior Representative

Cheminformatics, GSK
Senior Representative

 Why should you attend?
Get ready for the highly requested AI in Drug Discovery Conference this October 2024 in the United States. In the interim since our last gathering in March 2024 in the UK, the industry has achieved a groundbreaking milestone – the first wholly AI-discovered and designed drug is now undergoing Phase 2 clinical trials.

Four compelling reasons as to why you can't miss out:
• Gain insights from leading biotechs and big pharma on drug target selection
• Explore neural networks with a focus on digital twins, new drug designs and in-silico modelling to expand your portfolio
• Get the latest insights on the benefits of machine learning from molecule design to clinical trial selection, along with crucial patient-centric considerations.
• Discuss best use and potential impact of Generative AI in light of the launch of Chat GPT
Join us as we navigate through the hype and unveil effective strategies to harness the AI revolution for achieving tangible and transformative outcomes in the realm of drug design and discovery.

Benefit from the insights of our diverse speakers, leveraging their expertise to propel the field forward into clinical trials and introduce transformative new drugs to the market.

 Who should attend?
All companies wishing to get therapeutics to patients faster and thus extending healthy longevity for everyone.

Build your AI ecosystem combining internal and external resources and partners to discover new ways to treat diseases, design novel molecules, optimise pre-existing treatments, and reducing the cost & time of drug development.

Wish to share ideas, collaborate, and learn from successes and difficulties in both data science and drug discovery – fast-changing field that need interdisciplinary skills & experience.

Mature your company’s approach to AI and ML applications to hurdle the major challenges and avoid the pitfalls that caused previous failures in the first wave of initiatives. Benchmark your pipeline against the latest understanding of strengths and weaknesses in leveraging these tools.

Gain insight into the true nature of the major challenges – away from algorithms and tools, towards data and technical leadership.

Join us in October!


Director, Computational Biology, Cancer Immunology and Immune Modulation
Boehringer Ingelheim
Associate Director
Astellas Pharma
Co-Founder and CTO
Iambic Therapeutics
Head of Protein Design & Informatics
GSK
SVP of Business Development
Arctoris
CTO & Co-Founder
Envisagenics
President, Insilico Medicine Canada Inc., and Global Head of AI Platforms, VP
Insilico Medicine
Founder & CEO
Serna.bio
VP of Digital Chemistry
Recursion Pharmaceuticals
Director, Precision Labs
Genentech
Data Scientist, MLOps
Roche
Cheminformatics
GSK

VENUE

Courtyard by Marriott Boston Downtown

Boston, USA

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WHAT IS CPD?

CPD stands for Continuing Professional Development’. It is essentially a philosophy, which maintains that in order to be effective, learning should be organised and structured. The most common definition is:

‘A commitment to structured skills and knowledge enhancement for Personal or Professional competence’

CPD is a common requirement of individual membership with professional bodies and Institutes. Increasingly, employers also expect their staff to undertake regular CPD activities.

Undertaken over a period of time, CPD ensures that educational qualifications do not become obsolete, and allows for best practice and professional standards to be upheld.

CPD can be undertaken through a variety of learning activities including instructor led training courses, seminars and conferences, e:learning modules or structured reading.

CPD AND PROFESSIONAL INSTITUTES

There are approximately 470 institutes in the UK across all industry sectors, with a collective membership of circa 4 million professionals, and they all expect their members to undertake CPD.

For some institutes undertaking CPD is mandatory e.g. accountancy and law, and linked to a licence to practice, for others it’s obligatory. By ensuring that their members undertake CPD, the professional bodies seek to ensure that professional standards, legislative awareness and ethical practices are maintained.

CPD Schemes often run over the period of a year and the institutes generally provide online tools for their members to record and reflect on their CPD activities.

TYPICAL CPD SCHEMES AND RECORDING OF CPD (CPD points and hours)

Professional bodies and Institutes CPD schemes are either structured as ‘Input’ or ‘Output’ based.

‘Input’ based schemes list a precise number of CPD hours that individuals must achieve within a given time period. These schemes can also use different ‘currencies’ such as points, merits, units or credits, where an individual must accumulate the number required. These currencies are usually based on time i.e. 1 CPD point = 1 hour of learning.

‘Output’ based schemes are learner centred. They require individuals to set learning goals that align to professional competencies, or personal development objectives. These schemes also list different ways to achieve the learning goals e.g. training courses, seminars or e:learning, which enables an individual to complete their CPD through their preferred mode of learning.

The majority of Input and Output based schemes actively encourage individuals to seek appropriate CPD activities independently.

As a formal provider of CPD certified activities, SAE Media Group can provide an indication of the learning benefit gained and the typical completion. However, it is ultimately the responsibility of the delegate to evaluate their learning, and record it correctly in line with their professional body’s or employers requirements.

GLOBAL CPD

Increasingly, international and emerging markets are ‘professionalising’ their workforces and looking to the UK to benchmark educational standards. The undertaking of CPD is now increasingly expected of any individual employed within today’s global marketplace.

CPD Certificates

We can provide a certificate for all our accredited events. To request a CPD certificate for a conference , workshop, master classes you have attended please email events@saemediagroup.com

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