bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/192047

MICCS: A Fully Programmable Multipurpose Integrated Cell Culture System

Kassis, T.·Perez, P. M.·Yang, C. J. W.·Soenksen, L. R.·Trumper, D. L.·Griffith, L. G.
View original source ↗Export metadata ↓

Abstract

With the rise of research utilizing microphysiological systems (MPSs), the need for tools that enable the physiological mimicking of the relevant cellular environment is vital. The limited ability to reproduce crucial features of the microenvironment, such as surrounding fluid flow and dynamic changes in biochemical stimuli, severely limits the types of experiments that can be carried out. Current equipment to achieve this, such as syringe and peristaltic pumps, is expensive, large, difficult to program and has limited potential for scalability. Here, we present a new pumping platform that is open-source, low-cost, modular, scalable, fully-programmable and easy to assemble that can be incorporated into cell culture systems to better recapitulate physiological environments. By controlling two commercially available piezoelectric pumps using a Raspberry Pi Zero microcontroller, the system is capable of producing arbitrary dynamic flow profiles with reliable flow rates ranging from 1 to 3,000 {micro}L/min as specified by an easily programmable Python-based script. We validated the accuracy of the flow rates, the use of time-varying profiles, and the practicality of the system by creating repeatable dynamic concentration profiles using a 3D-printed static micromixer.

Source connections

Explore related subjects

bioengineeringPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kassis, T., Perez, P. M., Yang, C. J. W., Soenksen, L. R., Trumper, D. L., Griffith, L. G.. 2017-09-22. MICCS: A Fully Programmable Multipurpose Integrated Cell Culture System. https://doi.org/10.1101/192047

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

N-GLYcanyzer monitoring of a microperfusion process reveals critical parameters' impact on Trastuzumab biosimilar N-glycoform time evolution

Controlling monoclonal antibody (mAb) N-glycosylation as a critical quality attribute (CQA) remains challenging in continuous and intensified biomanufacturing, where conventional end-point analyses obscure dynamic pathway responses. Here, we deployed the N-GLYcanyzer process analytical technology (PAT) for automated monitoring of a microperfusion process that reveals critical parameters' impact on Trastuzumab biosimilar N-glycoform time evolution across a 20-day culture duration of Chinese Hamster Ovary (CHO) cells in a ~2 mL scale-down microbioreactor perfusion platform. Using offline PAT assays combined with our integrated at-line PAT workflow, we systematically screened six perfusion process parameters: carbon source, viable cell density (VCD), perfusion rate, temperature, and pH. While nutrient limitation and thermal/acidic stress significantly disrupted N-glycans maturation, notably triggering high-mannose (Man5) accumulation and severe productivity penalties under pH 6.7 and 39 {degrees}C operation, targeted feed supplementation with galactose and MnCl2 consistently shifted glycoform profiles away from G0F toward galactosylated species (G1F, G1F', G2F). Crucially, coupling this combined feed strategy with an intensified perfusion rate (1.2 VVD) achieved a sustained, desired galactosylation shift without a productivity cost. These findings demonstrate that nutrient feed composition and perfusion rate are primary levers for steering continuous intensified microperfusion processes for biologics production with desired N-glycoform states and highlight the utility of automated at-line PAT like N-GLYcanyzer for enabling real-time attribute-based control in continuous biomanufacturing.

bioengineering↗
bioRxiv2026

Differential sensing with imprinted and non-imprinted organic electrochemical transistors reduces calibration drift in wearable sweat cortisol sensors

The output of a wearable cortisol sensor drifts over days for reasons unrelated to cortisol, so a calibration made on the first day soon stops being valid. In our differential organic electrochemical transistor, a PEDOT:PSS transistor coated with a molecularly imprinted polymer (MIP) for cortisol is paired with one coated with a non-imprinted polymer (NIP) of the same composition, and the NIP response is subtracted. Over four calibrations in artificial sweat across 14 days, the response of the MIP alone shifted by 15% to 22% of its range on day 1, whereas the differential output shifted by 1% to 10%, and the variation between days at 1 to 10nM fell by 65% to 70% on average for individual pairs. In sweat from one participant, read against the calibration from day 1, both outputs tracked the direction of visible changes in salivary cortisol, while the MIP alone diverged from the differential output, consistent with the laboratory drift.

bioengineering↗
bioRxiv2026

A cytotoxicity dataset for data-driven design of ionizable lipid nanoparticles

Ionizable lipid nanoparticles (LNPs) are widely used to deliver nucleic acid therapeutics, but the design of safe LNPs remains challenging due to the complex activity relationships among structure, composition, and physicochemical properties. Here, we present a curated dataset, the Lipid Nanoparticle Cytotoxicity Database (LNPCD), which aggregates 1,413 LNP cytotoxicity measurements across 1,288 unique ionizable lipids drawn from 11 high-throughput combinatorial studies. Lipid structures were generated computationally from the published libraries and manually verified against the original publications. Each record pairs a machine-readable SMILES representation of the ionizable lipid with its measured viability endpoint and the associated experimental descriptors, including cell line, dose, and cargo type. The dataset provides a traceable resource for examining how ionizable lipid structure and experimental conditions relate to in vitro cell viability, and for developing and evaluating computational models of lipid nanoparticle cytotoxicity.

bioengineering↗