Building Otto: An open-source Franz diffusion cell autosampler for automating in vitro skin permeation studies

The Franz diffusion cell (FDC), widely used for measuring drug absorption across the skin, is usually operated manually. However, manual operation is not only labour-intensive and time-consuming, but inevitably introduces human errors and inter-operator variability. The requirement to perform regular sampling around the clock also presents a significant logistical challenge for researchers. Commercial FDC automation solutions are costly and require proprietary/bespoke FDC designs. To overcome these challenges, we have developed Otto as a customisable and affordable, aftermarket FDC automation solution, to be retrofitted to existing FDCs of generic specifications. Otto uses a modified cartesian 3D-printer as a gantry and adds liquid-handling capabilities using 3D-printed components and common, inexpensive laboratory consumables. Liquid samples are collected into standard autosampler vials. Capable of handling 100 samples per run, Otto supports a high throughput and integrates well with downstream analytical equipment, without modifying the FDC or the analytical equipment. Its programming is facilitated by OttoMate, a companion software application with a graphical user interface designed to generate human-readable code for Otto. Here, we describe the design, construction, operation and characterisation of Otto. To our knowledge, this is the first open-source, retrofittable FDC autosampler with such throughput.

Institutions

Publication Details

Journal
HardwareX
Published
2025-12-21
DOI
https://doi.org/10.1016/j.ohx.2025.e00735
Primary Topic
Advancements in Transdermal Drug Delivery
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Building Otto: An open-source Franz diffusion cell autosampler for automating in vitro skin permeation studies

HardwareX
Advancements in Transdermal Drug Delivery
article

Building Otto: An open-source Franz diffusion cell autosampler for automating in vitro skin permeation studies

article en

Abstract

The Franz diffusion cell (FDC), widely used for measuring drug absorption across the skin, is usually operated manually. However, manual operation is not only labour-intensive and time-consuming, but inevitably introduces human errors and inter-operator variability. The requirement to perform regular sampling around the clock also presents a significant logistical challenge for researchers. Commercial FDC automation solutions are costly and require proprietary/bespoke FDC designs. To overcome these challenges, we have developed Otto as a customisable and affordable, aftermarket FDC automation solution, to be retrofitted to existing FDCs of generic specifications. Otto uses a modified cartesian 3D-printer as a gantry and adds liquid-handling capabilities using 3D-printed components and common, inexpensive laboratory consumables. Liquid samples are collected into standard autosampler vials. Capable of handling 100 samples per run, Otto supports a high throughput and integrates well with downstream analytical equipment, without modifying the FDC or the analytical equipment. Its programming is facilitated by OttoMate, a companion software application with a graphical user interface designed to generate human-readable code for Otto. Here, we describe the design, construction, operation and characterisation of Otto. To our knowledge, this is the first open-source, retrofittable FDC autosampler with such throughput.

HardwareXVol. 25
Newcastle University (GB)
Openalex Percentile: Top 66%
Advancements in Transdermal Drug Delivery
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.