What are typical data science methods that we are not yet using enough?
Which areas will become important in the future in terms of data science?

Today, I am interviewing Dacheng Liu from Boehringer-Ingelheim and talk about the different opportunities open for data scientists in the pharmaceutical industry and answer the different interesting points below:

  • How did you get into data science and what does “data science” mean to you?
  • What are typical data science methods that we are not yet using enough?
  • Which areas do you think currently have the biggest potential to benefit from such methods?
  • Which case studies do you have in mind?
  • Which areas will become important in the future in terms of data science?

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Dacheng Liu

Global Head of Clinical Data Sciences of Boehringer Ingelheim

Dacheng Liu is the Global Head of Clinical Data Sciences of Boehringer Ingelheim with 16 years of experience in pharma industry. He leads the global team of 230 clinical data scientists, including statisticians and programmers, which focuses on drug development life cycle activities, including early and late clinical development, and medical affairs and real-world data applications etc. At BI he led early/late-phase projects in multiple disease areas, including several landmark studies. He was experienced with various regulatory submissions and FDA advisory committee meetings.  He also led SOP process harmonization, and standardization of statistical methodologies within the company. He represents BI on industry-wide working groups, such as PhRMA clinical development working group. He has over 40 publications in areas of clinical research, statistical methodology and machine learning.

References: https://theeffectivestatistician.com/wp-content/uploads/2022/01/References.docx

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I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.

I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.

When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.

When my mother is sick, I want her to understand the evidence and being able to understand it.

When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.

I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.

Let’s work together to achieve this.