While pharma companies are increasingly realizing the value of data, they need to realize the importance of data mindset among non-data employees. Without the right mindset neither BI nor AI will be utilized. MSD has implemented a 3-year data literacy program to enable marketing and sales employees to understand customer data & insights and know how to use it. We are in the middle of this journey and will share the approaches we have used and our experience so far.
Dr. Steffen Wagner
German health insurance companies are obliged to check billings for accuracy. The effort involved is enormous and the use of machine learning promises great optimization potential. The talk presents the experiences made here by SpectrumK, a provider of data services for health insurance companies. It will be discussed that different regimes (e.g. drugs, hospital stays, home health care) come with different requirements for the machine learning technology used and how integration into existing processes can succeed.
Dr. Sebastian Wernicke
Over the past two years, ONE LOGIC supported a major Covid vaccine manufacturer and several government agencies in using data to reliably scale the Covid vaccine production and distribute doses to when and where they are needed. We believe this case study can be applied broadly across sensitive supply chains in biotech and pharma, but also on a global scale for issues like the current “chip crisis”.
We have created a new method based on the ROPRO (oncology prognostic score). Our method analyses the longitudinal response of patient cohorts to medications. We conducted a retrospective analysis, where we recreated clinical trials from a large real-world dataset and from real in-house clinical trials. Using this new method we detected the treatment benefit earlier than with established methodology. This case study is showing great promise as a clinical development decision support tool.
The Greater Manchester case study tells a compelling story about the collaboration around data sharing across a health system and utilisation of business intelligence technologies. Multiple health care providers work as a collective urgent care system, sharing system pressures using business intelligence and predictive analytics. The reporting is not only near live but also supports a view of department pressures above and beyond how many people are waiting for treatment. Predictive metrics enable proactive utilisation of directing ambulance flows to support each other as a system.
In our work, we created an AI and high-throughput imaging pipeline, which can help biologist to generate thousands of single cell images and analyze them in a short time. This pipeline assists biologist in designing, understanding the mode of action and predicting the efficacy of different antibodies.
Joao Teixeira Nogueira
SHAP is a great tool to help developers and users understand black box models. To push it to the next level, we will show how to leverage on Dash, SHAP, gifs, LSTM and auto-encoders to generate interactive dashboards with animations and visual representations to understand how different AI models learn and change their minds while progressively trained with growing amounts of data. We will show this application in the context of Chronic Kidney Disease prediction and broader Healthcare AI.
Healthcare is about people- the patients receiving care, the people delivering it and those creating ways to support this. Data via predictive analytics is an enabler to supports a healthcare provider or system to achieve operational excellence to help problems thus faced by the people. Doing this well not only delivers patient outcomes but supports preventative and proactive population health management. In this table discussion, we would like to discuss these questions: What is the connection between operational excellence, predictive data analytics and artificial intelligence? What are the driving forces for achieving organizational performance by using artificial intelligence? What are the barriers to achieving organizational performance using artificial intelligence?
Knowledge is everything!
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