Artificial intelligence in the pharmaceutical industry

Stay competitive with the use of data science and AI in your company. You already know what project you want to implement or want to find out what options are available? Our experts will help you from idea generation to implementation in your business.

DATA & AI PROJECTS FOR pharmaceutical companies

We have used our experience from over 1,000 projects in the last 8 years to develop a holistic system for Data & AI projects - our [at] Data Journey.A consistent data strategy forms the basis and the framework for using data efficiently in your company. The goal is to test use cases as quickly as possible in order to develop a prototype with real data from the concept. In the Data Factory, use cases are industrialised into a finished product. The absolute focus is on scaling and sustainable generation of added value - which is why the user is also the focus here. In our DataOps, we operate and maintain your platforms and machine learning algorithms.

Since our founding in 2012, we have developed into a leading provider of artificial intelligence, data science and big data in the German-speaking region. Together with our clients, we generate real added value from data. To do this, we develop and implement data-driven innovations as well as new business models. We empower our clients to develop their own strengths and accompany them on their journey with our [at] Data Journey - from data strategy to the development of Algorithms and the construction of IT architectures through to maintenance and operation.

Opportunities of AI for the pharmaceutical industry

new business models

Reduce development time

Development time of new drugs can be shortened

Complying with laws with AI

Data access

Access to all relevant data with a data warehouse

Improve user experience

Derive decisions

Make more effective and intelligent decisions

Reduce costs

Quick identification

AI assists in finding a suitable dose of active ingredient

new business models thanks to ki

Customer Experience

Measure patient satisfaction and treatment adherence

Expanding market share with AI

Reduce costs

Reduce resources through process automation

Projects of our customers

We have proven our data science and AI expertise in the pharmaceutical sector for various projects. Read some references on AI in the pharmaceutical industry here. If you have any questions, please feel free to contact us.

Determine drug position with AI

AI-based visibility of the medication position in the entire "cold chain

NLP for drug discovery and development

NLP-based text analysis to reduce the time needed for drug discovery and development

Prediction Quality Deviation AI Pharma

Timely prediction of unacceptable quality deviations

Risk assessment with NLP and text mining

Intelligent system for automatic adjustment of the parameters for material disposition

Medication approval

Drug approval delay based on centralised approval management

Roadmap workshop for insurance companies

Biopharmaceutical performance optimisation

Industry Exchange #KIpharma

AI in the pharmaceutical industry

Compared to other industries, the pharmaceutical industry has so far neglected artificial intelligence. Yet it is precisely here that many opportunities present themselves: AI can predict reactions - and even suggest reactions that produce certain active ingredients. In our Industry Exchange, experts from the pharmaceutical sector came together and talked about the opportunities, challenges and also the reasons for the comparatively hesitant use of AI so far. The discussion also covered regulatory and ethical requirements. And ultimately also about encrusted leadership cultures in an established industry. Take a look at our Industry Exchange #KIPharma at any time and free of charge.


IQVIA research highlights ten potential areas, including the use of digital applications in healthcare, artificial intelligence (AI) and machine learning (ML), next-generation biotherapeutics and health practice insights.

According to this research, the use of artificial intelligence and machine learning will soon become the norm for life science companies. Currently, the most advanced method is to use intelligent algorithms to analyse large and complex amounts of data, especially in clinical and preclinical research. The algorithm is used to test preclinical drug candidates for new drugs and identify potential targets based on utility data. Overall, they have been found to improve the efficiency of clinical development. However, to better subdivide patient groups or better identify undiagnosed patients, predictive analysis supported by ML can be used.

According to IQVIA, the US Food and Drug Administration (FDA) is receiving more and more requests to approve mobile apps for therapeutic purposes. These digital therapies (DTx) require prescriptions and the use of digital technology for treatment. They are expected to make significant advances, especially in the areas of health behaviour and cognition. On the other hand, the evaluation of new treatments by other stakeholders is more rigorous, as their benefits have not been proven in practice.

More examples
- Information about competitors can be collected, analysed and prioritised more quickly
- Chatbots provide automated feedback to patients and healthcare providers
- Patient cohorts can be identified and thus recruited for research studies
- Advanced analytics helps identify suitable medicines more quickly for alternative applications

Download Whitepaper

- Artificial intelligence in medicine -

Why with [at]


Leader for AI and Big Data

We have been recognised as a #1 Value Creator in Machine Learning by CRISP Research and as a Big Data Leader in Germany by Experton.

Technology-independent consulting

We are manufacturer-independent. We find the right technology for our customers depending on their needs and support them in the implementation.

Expert for pharmaceutical companies

We have successfully completed over 1,000 AI & Data Science projects, including over 50 in the pharmaceutical industry.

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Simon Decker

Simon Decker

Data & AI Projects Medicine & Pharma

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