Bioprocess Engineering
© TU Berlin/PR/Felix Noak
KIWI Biolab


The KIWI Biolab focuses on automated methods and model-based bioprocess engineering. Our main goal is to find optimal process conditions for biotechnological applications. For this purpose, pipetting robots / liquid handling stations are combined with process models and machine learning approaches. By combining automation and modeling, highly complex tasks can be performed quickly and precisely that would not be possible manually.

The KIWI Biolab is dedicated to a broad spectrum of biotechnological process development from library screening to conditional screening under scale-down conditions. The development and application of mechanistic models represents a large part of the research group. In the context of collaborations, hybrid models and machine learning are increasingly becoming the focus of our work. The developed models are used for process monitoring as well as for process control (model predictive control). In addition to the model-based methods, the HT lab is the heart of this research group. With the establishment of this lab, the KIWI Biolab has acquired great competences in automation, integration of lab equipment and software engineering. This knowledge is contributed to various projects and to the SiLA consortium.

Group Lead

The KIWI biolab is headed by Dr. Mariano Nicolas Cruz Bournazou.

He holds a bachelor degree in Chemical Engineering and a PhD in the field of Model Based Optimization of Bioprocesses from the TU Berlin. His international experience includes research stays at Texas A&M (process control laboratory, Prof. Kravaris) and ETH Zurich (Morbidelli group). The research of Dr. Cruz is focused in the fields of bioprocess digitalization, model-based tools for biotechnology and biopharma, High Throughput Bioprocess Development, and autonomous biolabs. In recent years, his research has pushed the integration of model-based methods and High Throughput experiments to accelerate bioprocess development. The most relevant achievements include the first adaptive algorithms for online optimal redesign of parallel experiments and novel hybrid (Machine Learning and dynamical modelling) tools for bioprocess engineering. The driving force of his research is the conviction that robotic systems need proper digital tools, models, and algorithms to fully exploit its capabilities in bioprocess development and biomanufacturing. 

Automation and digitization

The automation and digitization of biotechnological processes and laboratories is not an end in itself. It is the prerequisite for a successful transformation towards a green economy. At the latest with the launch of the AutoBIO project in 2012, the KIWI biolab has become one of the leading groups in this field in the field of biotechnology. Together with our partners, such as Siemens, DataHow, labforward or Düperthal, we work on innovative digital solutions and case studies. The KIWI biolab with its pipetting robots, integrated lab equipment and software solutions provides an ideal ecosystem for developing and testing sophisticated applications. The KIWI biolab has developed high competencies to accompany or walk every step of automation and digitalization.

© Philipp Arnoldt


The HTBD - Groupe offers various lectures dedicated to the basics of our work. You can find an overview of our current courses here.

Model based automation and model predictive control

Model-based automation is the crucial step towards smart bioprocesses and smart plants. We use mechanistic and data-driven models to map bioprocesses and make predictions about what will happen next. This knowledge is used for optimal online redesign of experiments. The accuracy of our models is ensured by online adjustment of model parameters, and the precision of our predictions is ensured by sensitivity analyses. All this is done in an automated environment where devices, computational applications, and data can communicate with each other in a targeted manner. Using state-of-the-art machine learning tools, the process planning and execution of tomorrow is developed here and in projects such as in KIWI-biolab, MESSINA or AMADEUS.

© Dominic Simon

Opportunity / Thesis

Are you looking for a challenging thesis? We often have open topics! Send us your interests and strengths together with a short CV via email.

Running Projects

© TU Berlin/PR/Felix Noak


Project Partner: Boehringer Ingelheim Vienna
Robust adaptive model-based design of experiments for high throughput bioprocess development


Project Partner: C-Cis Sensors AG
Development of a high-throughput at-line glucose sensor

© TU Berlin/PR/Felix Noak


Project Partner: DataHow AG, labforward GmbH
Development of a platform for the automated robotic optimization of bioprocesses


development of a miniature multi-bioreactor system for the purpose of speeding up bioprocess development


Project Partner: Universtät Hildesheim, Universität Greifswald
Internationales Zukunfslabor für KI-gestützte Bioprozessentwicklung

© TU Berlin/PR/Felix Noak


Project Partner: Wacker Biotech
Model based Scale-Down experiments for a convertible high throughput screening framework


VLB: High Gravity Beer

Projet Partner: VLP Berlin
Development and Characterization of a fed-batch fermentation process for high gravity brewing

The Lab