Development of a high-throughput bioreactor system for biomedical applications

1. Mazzei Daniele Interdepartmental Research Center “E.Piaggio” Development of a high-throughput bioreactorsystem for biomedical applications

2. TissueEngineering • Aim: • Transplant • PharmacologicalTesting • ArtificialOrgans Basic steps • Biopsy • Cells extraction • Cell seeding • Cell Growing • Cell monolayer

3. High Throughput Screening (HTS) • HTS, is a method used in experimentation , such as drug testing • Is based on a brute-force approach to collect a large amount of experimental data in a short time and with few animals • HTS is achieved nowadays using multi-well equipment that contains cell cultures

4. ? Does it work? • The multi-well system presents a principal problem, the environment discrepancy problem, that affects the relevance of tests • the environment discrepancy problem implies that the collected data are not directly usable in drug tests, because the cell monolayer grown in wells is only a brutal approximation of biological reality • This seems to be a paradox since the multi-well has been the core element of the HTS

5. Our Idea • A bioreactor is a system able to maintain a cell culture in a • controlled environment, that mimics a living organism.

6. The Bioreactors • A bioreactor is a more realistic approximation of in-vivo Physiology. • Bioreactors have not been designed for HTS • We present a new bioreactor, called MCB, able to perform HTS experiment in a in-vivo-like simulated environment for long time

7. The MCB System • The MCB bioreactor system consists of the following parts: • Cell culture chamber • Mixing chamber • Electronic board and electro-valve system • Peristaltic pump, PC • Heating system

8. The mixing chamber • The mixing chamber allows regulation of pH and Oxygen flow • The medium is perfused with gas according to the measured pH • pH regulation is performed by inlet of two different gases : CO2 and Air

9. The Control System • The micro controlled board runs the μTNetOS operating system • The goal of this application is to realise an autonomous bioreactor by a real-time control of environmental variables

10. µTNetOS void TimerDoStep(Timer* t) { Heap *h = &t-> priorityQueue; while (h->pos && heap_Top(h) ->val <= GETTIME()) { HeapElement e = heap_Remove(h); int d = e.task->nextState(e.task); if (d) { e.val = GETTIME() + d; heap_Insert(h, e); } } } • μTNetOS is a generated operating system: • the system generator takes as input the description of an XML based protocol, • The system uses cooperative multi-tasking to run concurrent activities • μTNetOS is based on a robotics programming framework called Robotics4.NET

11. Robotics4.Net and the Bioreactors The framework proposes a software architecture inspired to the architecture of the human nervous system. • The Brain: The core of control system • The Bodymap: A sort of black board used to send and receive messages • The Roblets: The appendix of the system, as the parts of our nervous system, read data from the environment and convert the Brain signal into an action

12. The High Throughput Bioeactor • A High Throughput bioreactor experiment, employs many bioreactors with different cell culture chambers • The network connections allows remote monitoring of experiments (through Internet) • A pathology can be simulated in one of the Bioreactor, and the others can be used as control • Grazie a Robotics4.Net ogni bioreattore sarà visto come un sistema autonomo • Attraverso il PC sarà possbile controllare più bioreattori • Il controllo del sistema rimane però a bordo del bioreattore

14. The user interface • The Graphical User Interface is developed in C#.Net • It is based on a multi tab structure • GUI is used to read data from the bioreactors and to setup the experimental variables • There are tools for sensor calibration • Manual control is possible

15. Preliminar Controll Results • 48h parallel experiment with 4 bioreactors The data extracted from the bioreactors during the experiment shows how the new system is able to correctly control the environmental variables

16. Preliminar Controll Results Endothelial cells (HUVECS) on a laminar flow culture chamber after 48h • We can observe the morphology of the cells, they do not show any type of cell membrane damage • We can use the cells as sensors of the environment, in the micrograph we can observe how the endothelial cells, are oriented with the medium flow and have an elliptical shape similar to their in-vivo morphology.

17. New Modular MCB Chamber • Same dimension of Multiwell • Modular connection in serie and parallel configuration • Easy to use • Microfluid-dynamic modelled

18. New Modular MCB Chamber

19. New Modular MCB Chamber 1mm inlet , 2mm outlet 1mm Inlet and Outlet Velocity reduced of 0,005 m/s !

20. New Modular MCB Chamber

21. Howtocontrol pH • pH = -log10[H+] • H2O + H2O  H3O+(aq) + OH-(aq) • The culture medium is added with a Buffer • A buffer is a solution able to stabilized the pH of a liquid • Phosphate buffer  H2CO3/HCO3Is a water solutionofCarbonic Acid and sodiumbicarbonate NaHCO3. • Key Points: • The Solubility of Oxygen in water is very Low • The Solubilityof Carbon Dioxide in water is very High • Water + O2  pH increase slowly • Water + CO2 pH decrease very fast

22. Howtocontrol pH CO2 + H2O  HCO3- + H+ 4H+ + OH-+ O2 2H2O + OH- • High delay • Only few CO2 mole decrease pH • High risk for cell culture! • CO2 and O2 kinetich are very different Impossible to use a simple On-Off Controll! Impossible to find a controll transfer function!

23. ASM Environment Simulator • Developed of an ASM Environment Simulator • Simulate the fluid/gas environment • Testing the pH controll algorithm

25. Interdepartmental Research Center“E. Piaggio” Bio- Group Arti Ahluwalia Giovanni Vozzi Federico Vozzi Bruna Vinci Daniele Mazzei Francesca Montemurro Carmelo De Maria MariangelaGuzzardi http://dionisio.ing.unipi.it