Bachelor or Master Thesis on "Pharma and AI"

We are currently looking for students wanting to write their BA or MA thesis on the impact of artificial intelligence (AI) in the pharmaceutical industry. Please find detailed information on the topic below.

Topic: Risks with Artificial Intelligence

Research and development (R&D) is a risky endeavour for pharma companies. The average success rate of pharmaceutical R&D is around 4%, while 96% of R&D projects fail due to lack of efficacy, toxicity or other reasons. Pharma companies use new technologies, such as AI, to reduce R&D-associated risks and to increase the efficiencies of their R&D organizations. But what are the risks associated with using AI?


Scope of the thesis:
In your project, you will set-up a risk matrix for pharma R&D and use this matrix to evaluate the risk potential of machine learning, big data and AI. Concrete you will answer the questions: Can machine learning, big data and AI reduce risks of pharma R&D? What are the concrete applications and how can they have an impact on risk? And what are the risks associated with using machine learning, big data and AI in pharma R&D?


Your profile:

  • Theoretical background of the pharma business
  • Organized, conscientious and result-oriented working attitude
  • Very good communication and written skills in English

Topic: Does science translate into pharma success?

Pharmaceutical companies, such as Novartis or Roche, are among the top investors in research & development (R&D) worldwide and across all industries. On average, they invest up to USD billion 9 annually to discover and develop new drugs/medicines. Next to strategies or management process, science is a major differentiator in the market success of these research-driven companies.


Scope of the thesis:
In your project, you will analyse the scientific performance of top 20 pharma companies (and parent companies) for the last 25 years and try to correlate the results with the outputs (viz. Number of new drugs launched) in that time period.


Your profile:

  • Practical experience in managing and analysing big data sets
  • Organized, conscientious and result-oriented working attitude
  • Very good communication and written skills in English

Topic: Success factors of AI start-ups

Starts-ups entering the pharma arena transform the sector by artificial intelligence (AI). Wearables, virtual assistants, AI in research, drug discovery, mental health, genetics/genomics, patient data management or risk management are only some of the examples of new entrants that impact the pharma business.

 

Scope of the thesis:

In your project, you will characterize start-up companies such as Atomwise, Cyclica, DeepMind Health, Exscientia, Insilico Medicine, Numerate or Recursion Pharmaceuticals and analysis their funding, technologies, products, services, core competencies and partnerships. By doing so, you will evaluate what makes a successful AI start-up and what differentiate it from less successful peers.

 

Your profile:

  • Theoretical background of the pharma business
  • Organized, conscientious and result-oriented working attitude
  • Very good communication and written skills in English

Applications

Interested students should send a copy of their CV and grade transcript to Naomi Haefner.

Naomi Haefner
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