DAY ONE - September 25th 2019

7.50 am               Registration and coffee

8.40 am               Opening address from chairperson

8.50 am PRESENTATION: KEYNOTE ADDRESS

The Big Picture: Why Getting Data Right Is So Important For Pharma

  • What are we fixing? What is the current problem? What are the drivers for change?

  • What’s required to fully embrace data-driven decision making and drug development at executive level?

  • Top-level strategies for implementing and improving the efficiency and effectiveness of data-driven approaches.

  • Bottom-up: Considering the needs of end users and developing a clear vision & strategy to manage transition.

  • What the main challenges in the context of data are culturally and ethically, not technically.

9.20 am               PRESENTATION: ANALYSIS AND INSIGHTS

A Critique of The Existing Data Life Cycle, How To Achieve Scale And A Vision For The Near- And Mid-Term Future

  • Garbage in, garbage out: Why current spending on data capture and analysis can be flawed, and how to derive true value.

  • The capture > storage > catalogue > analyse > share life cycle, and how pharma can transition from data > information > knowledge > wisdom.

  • The importance of data organisation, enrichment and context in building robust processes and infrastructure that are more scalable.

  • How to optimise the process for a variety and volume of use-cases, while reducing error rate and costs.

9.50 am               SPEED NETWORKING

Brief introductions with other meeting participants in a snappy, friendly format. A managed session, giving you the chance to quickly establish who else is in attendance and exchange business cards with potential partners and collaborators.

10.40 am             Morning break and coffee

11.00 am             PRESENTATION: SECURING BUDGET

Building and Making the Business Case For Investment And Executive Attention/Focus On Better Processes And Infrastructure

  • Developing an awareness of compelling factors, including scientific/clinical need, environmental factors (ethos, company context, leadership changes) and required ecosystems

  • Understanding the benefits of investing to make data FAIR

  • Considerations for making the business case and securing investment,

  • Scale and the importance of adaptive infrastructure, including supplier considerations.

  • Understanding the importance of ROI metrics.

11.30 am             TECHNOLOGY SPOTLIGHT

A ten-minute presentation outlining a new technology that will disrupt or positively impact data-driven drug development.

11.40am             CASE STUDY: SECURING BUDGET

Winning The Investment Case, And What Happens Next

  • Learning from a specific case study example.

  • How did the case evolve throughout the build, delivery and getting the green light?

  • What were the factors that led to a successful outcome?

  • What were the important tenets of the business case in the eyes of the executives?

  • Lessons learned re. culture and how change was received within the organisation.

  • A brief discussion on ROI metrics (and actual ROI if possible).

12.10 am             ROUND TABLE DISCUSSIONS

Considerations For Making The Business Case, Managing Next Steps And Improving The Success Of Implementation

Ideas and innovation are important, but with pharma and data there is a clear disconnection between ideas and business reality. Making change happen in a fast-moving organisation is difficult.

Improving (often) antiquated systems and processes for bio-data collection, management, analysis and interpretation so that they are fit-for purpose in the new-age of data will mean winning the business case for investment with executive teams.

Attendees will break off into round-table discussions to discuss how to build, make and win the business case for investment and change.  Notes will be taken, and the output from this session will be captured and structured into a summary report for attendees.

Points for discussion will vary, but might include:

  • Overall challenges, risk factors and lessons learned in winning the business case for such projects.

  • What are the criteria/tenets for making the business case

  • Scale and the importance of adaptive, sustainable infrastructure.

  • Supplier/partner considerations.

  • Learning from experience – factors that led to a successful outcome

  • Lessons learned re. culture and how change was received within the organisation.

  • How to demonstrate/project ROI.

12.50 pm            Lunch

1.50 pm              PRESENTATION: EMPIRICAL DATA ON DIRECTIONS AND TRENDS

 Learning from Pharma Industry Metrics and Benchmarking from PRISME

  • An overview on the activities and goals of PRISME – the Pharmaceutical R&D Information Systems Management Executives forum

  • Directions and trends in R&D IT management and technology

  • What the results mean for best practices to facilitate drug R&D in pharma 

2.20 pm              PRESENTATION: MAKING DATA FAIR

 What to do About FAIR…

 In the experience of many pharma professionals, FAIR remains fairly abstract, bordering on inconclusive. This session will outline specific case studies – real problems with real data, and address opportunities and real concerns.

  • Why making data Findable, Actionable, Interoperable and Reproducible is important.

  • “If FAIR data has a value, somebody would pay for it”. Could it be that the value is not worth the cleansing? Contrasting the ideal with the reality.

  • Moving forward: How can FAIR work best in a commercial context?

2.50 pm               TECHNOLOGY SPOTLIGHT

A ten-minute presentation outlining a new technology that will disrupt or positively impact data-driven drug development.

3.00 pm               PRESENTATION: VALUING DATA

How to Assess the True Value of Bio-Data in the Context of Pharma

  • Why has it become increasingly important to assess the value of data? The important questions to ask.

  • Factors that influence the value of data.

  • Getting involved: Next steps in a collaborative experiment to build a model for assessing the value of data.

3.30 pm               Afternoon break and coffee

4.00 pm              INNOVATION SHOWCASE

The innovation showcase is an interactive session, designed to deliver you the most innovative breakthrough technologies affecting data-driven drug development. Each presentation lasts 10 minutes, and at the end of the session, the audience vote for the technology/presentation that they think will have the greatest impact.

  • Talk 1 (10 minutes)

  • Talk 2 (10 minutes)

  • Talk 3 (10 minutes)

  • Talk 4 (10 minutes)

The winning technology will receive an award for ‘voted most innovative technology at D4’.

5.00 pm              PANEL DISCUSSION: DATA VALUE, THE DATA ECOSYSTEM AND TAKEAWAYS

 A summary of the day’s discussion and take-home intelligence/insights. Topics will be taken from the audience, but might include:

 Data Value

  • How can you define metrics for the “value” of a dataset?

  • Cracks between departmental cultures: who understands how much it costs to cleanse data? Who does it?

 Pharma Ecosystem Alignment in a New Data-Driven World

  • Regulators: Data calls for iterations and speed. But regulation struggles with fast pace. How to manage a potential disconnect, and what should the future look like?

  • Privacy issues: The world of biodata/AI is exploratory. Most consent is for “specific purposes”. How do the two fit together?

  • Future considerations: Do we need a new, overall model for data/information in medicine, if it’s use/housing not going to be limited to pharma anymore?

 Capturing the Main Takeaways and Useful Next Steps from Today

  • A discussion of whether the meeting met objectives. If not, what’s missing – a brief discussion on those points.

  • What would be the useful next steps, focus areas and/or meet-ups?

5.30 pm               Closing remarks

5.40 pm               Drinks reception and “hands-on” innovation showcase

7.00 pm Dinner at a local restaurant for those who have signed up - please sign up at the registration desk on the day. A final opportunity to network with other attendees in an informal setting.


DAY TWO - September 26th 2019

8.50 am               Opening address from chairperson.

9.00 am               PRESENTATION: KEYNOTE ADDRESS

Data Driven Drug Development

  • The importance of taking a scientific approach to industry challenges.

  • How have data driven approaches developed throughout the field of genomics.

  • What are the main objectives of the day?

9.30 am               PRESENTATION: DISCOVERABILITY

Case Study: Learning From Efforts To Make Data More Discoverable

  • Who are the important stakeholders in optimizing discoverability processes? Considering the end users who need to find and discover data.

  • Where are the date sets in our enterprises?

  • Addressing data ownership, governance and permission to find data, including access frameworks.

  • Why the discoverability process has been historically underestimated, and what to do about it.

  • The role of automation and enterprise systems in ensuring transparency and navigation of data.

10.00 am             PRESENTATION: INTEGRATION AND INTEROPERABILITY

Case Study: Overcoming The Combinatorial Nightmare: Advances In Interoperability And Integration Of Diverse Data Sets

  • Moving beyond single-dimension analysis: Why should systems be interoperable?

  • Case study examples on how effective interoperability and integration has led to success pharma outcomes.

  • A brief discussion of structured versus unstructured data and implications for integration and analysis.

  • Infrastructure considerations of users and culture through the adoption of ML.

10.30 am             Morning break and Coffee

11.00 am             PRESENTATION: SUPPORTING STRATEGIC DECISION-MAKING RELATING TO AI

Crash Course in AI for Leadership Teams in Pharma

This session will simplify key AI concepts to help leadership team to connect the dots in the value chain in their organization. It will help attendees appreciate the hype and hope areas of AI, enabling senior business, IT, data and research leaders to make better strategic decisions around the use of AI in various aspects of drug development. The session will both demystify AI and debunk AI myths that prevent organizations and senior-level people from moving forward in making the right decisions

11.30 am             PRESENTATION: A GROUND-BREAKING AI-LED PLATFORM

A Technology-Led Perspective on AI/ML-Driven Drug Development

This session will provide the technology-led perspective of a leading AI platform developer in the space, to compliment the perspectives of drug developers.

12.00 pm            PRESENTATION: BUILDING DATA VALUE VIA ML/AI TECHNOLOGIES

Capitalizing on The Emerging Role Of ML/AI-Driven Technologies as Relevant for Data Capturing and Processing to Build Value

  • Roles for AI/ML in optimizing each element of an improved data lifecycle, and what this means for making a business case and managing change.

  • Why improvements in ML and adoption of ML approaches are a necessity for pharma in generating business-wide value and ROI.

  • Why organization/structuring of data and fully leveraging ML go together.

  • Careful consideration of end users and culture through the adoption of ML.

12.30 pm            Lunch

1.30 pm              PANEL DISCUSSION: PHARMA SCIENTIFIC PROGRAM LEADERS

 How Did We Get Here, Where Do We Go Now?

  • Why is there such a difference in approach to application of data-driven approaches within pharma R&D?

  • If pharma is a copycat industry, what is going to be the big success that forces the rest to follow?

  • How do you scale up efficiently, and begin to seriously look at integrating multi-omic and real-world data?

2.00 pm               TECHNOLOGY SPOTLIGHT

A ten-minute presentation outlining a new technology that will disrupt or positively impact data-driven drug development.

2.10 pm               PANEL DISCUSSION: FROM CONCEPT TO EFFECTIVE EXECUTION

Panning for Gold

  • Separating the ‘useful’ from the ‘interesting’ in research.

  • How do you turn Machine Learning and Big Data in pharma, from sexy to applicable?

  • Solving data access challenges and understanding how to scale up and generate the right kinds of data.

2.40 pm               Afternoon break and coffee

3.10 pm              CASE STUDY: LEVERAGING GENOMIC-DATA IN AN INTEGRATIVE CONTEXT

Applied Genomics in Drug Discovery and Development

  • Practical examples of successful integration of genetic analysis in drug development and discovery.

  • Detailing the successes in eliminating inefficiencies, and opportunities around biomarker identification, target discovery, translational research, and trial enrolment and stratification.

3.40 pm               PANEL DISCUSSION: CLINICAL PROGRESS

Applying Data Approaches to Make Clinical Trials Work for You

  • What opportunities are in the freezer full of samples?

  • What will be admissible to support regulatory approval?

  • How can you make effective use of data to bring down the cost and increase the success of clinical trials?

4.10 pm               Closing remarks from chairperson

4.20 pm              Close of conference