HardwareX

The expanding scope of laboratory automation increasingly demands systems that can be tailored to specific experimental constraints, including footprint, timing, cost, and control. While open-source software has improved protocol flexibility, liquid-handling hardware itself remains largely closed, limiting the ability of academic and startup laboratories to build instruments around biological requirements rather than vendor defaults. Here, we present a fully open-source, purpose-built liquid-handling robot assembled from commercially available components and developed entirely in a research setting. The platform integrates open hardware, electronics, and a Python-based control stack compatible with PyLabRobot, exposing low-level motion dynamics and liquid-handling behaviors directly to experiment code. We validate the system using a high-throughput turbidostat workflow that requires rapid, closed-loop measurement and actuation to maintain microbial cultures at defined density setpoints. The robot sustains stable steady-state growth across approximately 200 cultures with heterogeneous growth dynamics. A replica build completed by two lab members in approximately one week confirms that the platform can be reproduced from its bill of materials and assembly guide. Its compact footprint and use of off-the-shelf components make it suitable for rapid, parallel deployment in settings such as public health emergencies or by distributed laboratories. Together, these results demonstrate that industry-class liquid handlers can be custom-built for specific experimental goals, establishing a blueprint for open, purpose-driven hardware development across research and industrial automation contexts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/709168v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1b2cb4eorg.highwire.dtl.DTLVardef@1418e8dorg.highwire.dtl.DTLVardef@f60618org.highwire.dtl.DTLVardef@a3d3b_HPS_FORMAT_FIGEXP M_FIG Open Liquid Handler (OLH) Design Goals. Left: Design goals for a purpose-built platform for time-sensitive, closed-loop biological workflows, emphasizing high-accuracy dosing (low variability liquid handling), rapid integrated measurement (plate deck and isolated workspace), customizable deck and peripheral options, compact footprint with high throughput, containment via an enclosed wet workspace for biosafety and sterility, and a replicable build using off-the-shelf OEM components with open design files. Right: Open Liquid Handler design and physical implementation, with aerial and front views highlighting the enclosed cabinet and the working envelope over a compact deck. C_FIG

Collecting cells from zebrafish embryos for genotyping is critical to rapid research with these model organisms. The standard collection process is manual, labor-intensive, time-consuming, and requires a skilled person to perform it. To overcome this challenge, researchers are exploring the development of automated genotyping tools for live animals, which would significantly enhance the efficiency and accuracy of genetic screening in zebrafish and other species. The focus of this research was to optimize the Zebrafish Embryo Genotyper (ZEG), an automated system used for the rapid extraction of cellular material from zebrafish embryos. This system rapidly vibrates a roughened chip containing a zebrafish embryo to collect genetic material safely and efficiently. The aim was to improve the efficiency of DNA collection from the chips used with the ZEG by identifying the key factors that contribute to the process. First, the chips were modified to resolve issues associated with loss of sample volume from the chip wells due to evaporation during processing. Second, we experimented with three critical parameters - sample volume in the wells, the vibrational frequency of the system, and the operation time - on the quantity of DNA collected. The performance was evaluated by measuring embryo survival and quantifying the DNA collected. The sensitivity (previously 90%) of the DNA collection and embryo survival (previously 95%) of the were both found to be greater than 95% after optimization. The optimized design parameters (15 {micro}L solution volume, 2.4 V, and a 5-minute run with 5 s alternating on/off) provided a >50% increase in DNA collection compared to the previous designs and parameters. The proposed chip design and operation do not appear to cause any apparent adverse effects on the development or survival of the embryos.

Live-cell imaging (LCI) provides researchers the opportunity to understand biological phenomena at a temporal resolution and is achieved using dedicated imaging systems. These studies enable insight into dynamic phenotypic changes occurring in cells, which may otherwise be missed when studying fixed samples. Access to advanced microscopy is disproportionately available to researchers in high-income countries, whereas researchers in low-to middle-income countries (LMICs) are severely underrepresented in the adoption of such technologies. A major barrier to the dissemination of advanced microscopy centres around economic inequalities, with the cost of high-end imaging systems often being prohibitively expensive. Recognition of such disparities has motivated the wider microscopy community to manufacture frugal microscopes that are accessible to researchers in resource-constrained settings. The OpenFlexure Microscope (OFM) is an open source, customisable, 3D-printed microscope suitable for medical research and field-diagnostics. We have made adaptations to the OFM to enable its use for live-cell imaging in humid tissue culture incubators. By moving major electronic components outside of the microscope, we remove the risk of corrosion of the Raspberry Pi and Sangaboard used to operate the instrument. We tested four common 3D-printing polymer materials for increased thermal robustness and found ASA is the best plastic to print the main body of the microscope, offering both durability and image stability in 24- to 48-hour time course experiments. We have also created an optional 3D-printable weighted-hammock system to reduce external vibration artefacts during image acquisition. Critically, electronic modifications included custom extension cables from the motors and camera to the Raspberry Pi and Sangaboard, and the inclusion of 22 ohm ({Omega}) resistors to reduce the current to the stepper motors, preventing detrimental temperature increases inside sealed incubators during prolonged powering of the instrument. To remove dependence on WiFi connections for setting up timelapse experiments, we generated a simple application with a graphical user interface (GUI) that can be installed locally on a Raspberry Pi and is specifically designed for setting up timelapse experiments without extensive computational knowledge or experience. We validated our LCI-OFM adaptations with a 48-hour treatment of MDA-MB-231 breast cancer cells with the chemotherapeutic drug docetaxel, showcasing how the modified microscope can seamlessly feed into established bioimaging pipelines and generate biologically meaningful results. For researchers in LMICs, this adapted LCI-OFM provides new opportunities to study locally-relevant health challenges with timelapse microscopy, enabling deeper insight into biological dynamics and supporting the generation of preliminary data critical for securing grant funding and access to more advanced imaging systems in purpose-built regional imaging hubs.

Free-air warming systems are essential for simulating climate change in field conditions, yet most are not designed to meet UK or EU health and safety standards. We present the design and field deployment of a hexagonal Temperature-Free Air Controlled Enhancement (T-FACE) system that fully complies with these regulations. The system uses real-time, temperature-responsive control with multiple sensors to maintain a consistent temperature differential between heated and ambient temperature experimental plots. We describe its engineering design, performance, costs, and key operational challenges, particularly related to heater reliability under continuous use. We tested the T-FACE system during the winter months of a field sown wheat crop. Phenotypic evaluation showed effects of heating on heading date, plant height, spike length, and spikelet number, suggesting the system potential. This proof-of-concept provides a scalable, regulation-compliant approach for studying crop responses to climate warming under realistic field conditions.

Distributed manufacturing of open-source hardware shows potential to offer accessible, affordable, and customizable solutions for users in low-resource contexts. Their real-world adoption, however, depends not only on the availability of openly shared designs but also on their replicability when fabricated in different local contexts. This work investigates the replicability of open-source hardware through a practical design-driven approach, using the development and experimental evaluation of a two-piece open-source forearm crutch as a case study. Replicability was considered from early-stage design and evaluated by introducing controlled variations from distributed manufacturing contexts, e.g., material feedstock, manufacturing equipment, and fabrication strategies. Four batches of crutches were fabricated and assembled, using virgin and recycled filaments on small- and large-format 3D printers. After the qualitative evaluation, mechanical static load testing was performed following ISO 11334:2007, together with economic analysis. Comparable mean load-bearing and consistent failure behavior were achieved across batches, making them suitable for use in pairs. Limited cost variability was achieved, supporting repairability and product lifecycle extension. Beyond the specific case study, replicability of open-source hardware needs to be considered as an early-stage design constraint by developing products that allow for variability from local contexts and by including product-specific approaches to assess replicability during development.

Home cage monitoring (HCM) captures longitudinal animal behavioural data without human intervention. However, the systems complexity is rarely addressed in their design, increasing the risk of data loss, which wastes workhours, resources, and animal lives. To assess the feasibility of implementing modern, robust architectures in complex operant HCM paradigms, the VersatiLe Autonomous DevIce for Scheduled Learning Assessment Via Wi-Fi (VLADISLAV) was developed and employed to test cognitive deficits in the intracerebroventricular streptozotocin-induced rat model of sporadic Alzheimers disease (sAD). Reliability was modelled against a system architecture common in commercial HCM systems by modelling the failure rate of the devices critical components across typical durations of animal experiments. VLADISLAV assessed multiple cognitive dimensions of a rat model of sAD with automated, scheduled testing. Its design enabled simultaneous, redundant recording to multiple devices in real time, as well as batch remote control and supervision of tens of VLADISLAVs. VLADISLAV is estimated to reduce component failure rate [~]200-fold at {euro}40/device. Data loss due to system failure shouldnt be accepted as a normal occurrence and robust system design is an ethical imperative. VLADISLAVs robustness and utility demonstrate the potential of embedded networked systems, used in other industries and consumer electronics for over a decade. Today, the open source ecosystem enables cost-effective implementation of such architectures in HCM by biomedical researchers with no electronic engineering education, preventing data loss and facilitating researchers and technicians day-to-day work. Considering these findings, it is apparent that the implementation of modern architectures in HCM is long overdue.

Gel electrophoresis has been a cornerstone laboratory technique for decades, yet it is often viewed as cumbersome, costly, and has remained confined to laboratory settings. Recent advances in DNA nanotechnology have repurposed electrophoresis as a primary readout for some biosensing applications such as DNA nanoswitches, where a conformational change in a DNA structure indicates the presence of a target molecule. Conventional gel electrophoresis setups not ideal for such targeted applications, with moderate equipment cost, excessive reagent use, and time-consuming processes. Here, we adopt a reductionist, application-driven approach to redesign gel electrophoresis specifically for DNA nanoswitch-based detection. We present a fully 3D-printable mini gel electrophoresis system that incorporates conductive plastic electrodes, demonstrating performance comparable to conventional systems using platinum electrodes. By optimizing the inter-electrode distance and running parameters, our system resolves the on/off states of DNA nanoswitches in as little as one minute. We further show that the device operates reliably at low voltages, including when powered by a USB power bank, and even enables instrument-free nanoswitch readout using an LED with a cell-phone camera. Our design substantially reduces the cost, voltage requirements, material usage, operational complexity, and experiment time. These improvements make gel-based biosensing more practical outside traditional laboratory environments, paving the way for broader adoption of gel electrophoresis in point-of-care and resource-limited settings.

We report a 0.18 {micro}m CMOS lab-on-a-chip system that monolithically integrates a passive radio frequency identification (RFID) interface and an 8 x 8 array of capacitance sensors configured for measuring the capacitance change resulting from an overlying biological specimen. This lab-on-CMOS platform is designed to operate wirelessly, first in a harvesting mode in which on-chip power is generated via the inductive coupling of an on-chip antenna to an external antenna, and second, in a sense-and-transmit mode where the capacitance sensor array is scanned and the measured data are transmitted to the external antenna using the same on-chip antenna. This paper presents characterization results of the passive RFID interface and of the sensor core, the latter utilizing several test analytes. The proposed system will facilitate the integration and packaging of a large number of chips in wet environments, paving the way for the inclusion of lab-on-CMOS technology in standard bio-analytical lab practice.

Solid immersion lenses (SILs) enhance the spatial resolution of an optical microscope by increasing the effective numerical aperture (NA) without physical modification of the objective lens. However, SIL application remains limited by cost, fragility, and accessibility. We present a rapid, single-step fabrication process to create optical quality hemispherical SILs using consumer-grade UV-curable transparent resin which reduces material costs by over five orders of magnitude relative to commercial glass counterparts. Our method produced resin SILs within seconds which can be easily implemented into conventional microscopy setups for increasing the effective NA. Quantitative imaging of USAF resolution targets and histology muscle preparations demonstrated a resolution enhancement approaching theoretical limits and comparable performance to N-BK7 glass SILs. This enabled visualisation of features usually below the diffraction limit of low NA dry objectives at a fraction of the cost of otherwise required high-powered objective lenses. To demonstrate accessibility and translational potential, our workflow was taught in a practical tutorial of an international microscopy course, where non-expert participants successfully fabricated, characterised, and applied SILs within a single session, reporting high confidence in independent implementation. We established ultra-low-cost resin SILs as a practical, scalable option to enhance the spatial resolution of routine optical microscopes and as an accessible and cost-effective platform for optics education.

Longitudinal live cell imaging is valuable for characterizing dynamic morphological and phenotypic changes in biological systems. However, conventional approaches rely on manual microscope operation, which is labor-intensive, limits imaging frequency, and disrupts the cellular environment. These constraints reduce scalability, increase experimental variability, and restrict both the duration and temporal resolution of continuous imaging. Although automated imaging platforms partially address these limitations, existing solutions are often constrained by the cost, footprint, and inflexibility of in-incubator microscopes or stage-top incubators. Here, we present an automated in-incubator epifluorescence microscope designed for long-term operation. The system features a modular architecture with optional multi-fluorescence imaging, automated plate scanning, configurable light sources, and compatibility with multiple plate formats, including integration with fluidic automation devices. By positioning the light sources and control electronics outside the incubator, the platform improves thermal stability and long-term operational reliability. This approach enables continuous, high-frequency imaging over extended durations, providing a source of rich data for quantifying time-dependent tissue phenotypes, morphological remodeling, and transient biological processes.

1.Liquid crystal polymer (LCP) is commonly used in the electronics industry due to its favorable dielectric, thermal, and insulative properties. It has recently gained popularity in the medical field for these same reasons, as well as its biocompatibility, moisture barrier properties, and ability to be microfabricated into thin film flexible circuits or flex PCBs. While polymers such as polyimide and Parylene C remain more common for electronics encapsulation and flexible circuit fabrication due to their relatively lower barriers to adoption and history of use, LCPs superior moisture barrier performance and low risk of delamination make it a promising material for chronic use in medical devices. In this work, the moisture barrier properties of LCP are evaluated using in vitro accelerated aging over 59-61 weeks at 65-68 {degrees}C, corresponding to an equivalent implanted lifetime of 8.1 and 9.4 years at 37 {degrees}C for each of two sample groups: LCP as an electronics encapsulant and as a flexible circuit substrate. In the encapsulation group, relative humidity inside an encapsulation pocket was monitored over time with no noticeable change in humidity throughout the measurement period. In the flexible circuit group, impedance of laminated interdigitated electrodes was monitored over time, with an average decrease to 44% of the initial impedance value across all successful samples due to the moisture absorption of the LCP, which has remained stable for the latter half of testing. In both groups, no delamination was observed. These findings demonstrate that LCP is a viable moisture barrier for electronics in implanted medical devices for an estimated equivalent lifetime of at least 8.1 years.

Cellular organelles are not just static structures; they are highly dynamic and directly linked to cellular functions. Changes in their morphology can be early indicators of diseases. Recent advancements in light microscopy techniques have transformed organelle research from qualitative descriptions to precise, quantitative measurements, enabling nanoscale resolution, high-throughput image analysis, and live-cell compatibility. This enables accurate measurement of organelle morphology, dynamics, and spatial organization using modern imaging and analysis techniques. By quantifying organelles, we go beyond simply visualizing to measuring and statistically comparing cellular features across different samples. This protocol addresses a wide range of cellular organelles across all major experimental systems, specifically mentioning mitochondria, myofibers, actin filaments, endoplasmic reticulum, and Golgi apparatus, by integrating experimental design, optimized sample preparation, high-resolution imaging, and validated Fiji/ImageJ-based analysis workflows. For each organelle, step-by-step methods specify reagents, equipment, acquisition parameters, and expected results. While recent advances, such as expansion microscopy, correlative light-electron microscopy, and AI-powered segmentation, offer gains in throughput and resolution, this workflow demonstrates that Fiji-based analysis remains fully capable of delivering high-precision organelle quantification. The entire workflow can be completed within 2-4 weeks, from initial design through validation and the production of measurements suitable for cross-study comparisons. Overall, this protocol establishes a flexible approach to standardize organelle quantification to understand multiple organelles simultaneously in their cellular contexts. Basic Protocol 1: Mitochondrial Quantification Basic Protocol 2: Myofibril Quantification Basic Protocol 3: Golgi Apparatus Morphometry Basic Protocol 4: Endoplasmic Reticulum Network Analysis Alternate Protocol 1: Super-Resolution Imaging Protocol

Cell viability is a critical parameter in bioproduction, yet most facilities still rely on manual, offline assays. This work introduces a new label-free Digital Holographic Microscopy (DHM)-based viability prediction pipeline using a simple optical design compatible with both on-line and in-line probe implementation. Unlike previous approaches validated under controled laboratory conditions, the proposed pipeline was designed to operate across diverse CHO bioprocess conditions without calibration or parameter tuning. It was validated on a large, heterogeneous dataset comprising 40 cell cultures collected from industrial and academic sites, spanning multiple cell lines, culture media, process modes and cell densities up to 100 million cells/mL. Beyond viability estimation, exploratory analyses suggest that DHM-based monitoring can provide additional process-relevant insights, including early detection of viability decline and correlation with recombinant protein titer. Together, these results indicate that DHM has the potential to enable a new generation of non-invasive, multiparametric monitoring tools for advanced bioproduction control.

1.Adipocyte size is an independent predictor of several metabolic disorders, including type 2 diabetes, liver and cardiovascular diseases. However, technical limitations due to the fragile nature of mature adipocytes have restricted the functional analyses of size-separated adipocytes using conventional methods. Therefore, we have developed a microfluidic device, based on deterministic lateral displacement, for sorting intact, mature adipocytes. Cell-size distribution was determined from time-lapse recordings inside the device, in separate outlets, and by Coulter counter analysis of the collected cell fractions. This approach allowed size-separation with minimal size-overlap with mean diameters of (small fraction) 47 {micro}m and (large fraction) 82 {micro}m based on Coulter counter measurements. Viability of the separated cells was verified by insulin stimulation and western blotting of key insulin signaling proteins. The sample recovery, comparing input versus output material, was relatively high, 42% for the large fraction with a purity of 93%. We demonstrate that microfluidics is a suitable approach to overcome the limitations of sorting mature adipocytes according to size. Together, the high recovery rate, high throughput capacity, accurate separation and the fact that the cells maintained hormonal response after sorting provides compelling evidence of the strength and usability of the microfluidic approach for exploring adipocyte function in relation to size.

This article presents the development of an advanced modeling and simulation platform for carbon capture systems, with a focus on integrated process analysis from upstream CO2 capture through to bioethanol production. The platform supports the evaluation of CO2 mitigation technology by coupling mathematical bioprocess models with an interactive desktop application. The biological system employs Chlorella vulgaris microalgae to fix CO2 through photosynthesis and generate carbohydrate substrates, which are subsequently converted to bioethanol by Saccharomyces cerevisiae yeast via fermentation. The simulation integrates three established kinetic models--the Monod, Logistic, and Luedeking-Piret models--to predict biomass growth, substrate consumption, and ethanol yield under varying operational conditions. A closed-loop CO2 recycling subsystem captures fermentation off-gases and reintroduces them into the bioreactor, enhancing overall carbon utilization efficiency. Three representative simulation scenarios demonstrated process efficiencies ranging from 1.09% to 93.78% of the theoretical maximum CO2-to-ethanol conversion efficiency, confirming the platforms capacity to evaluate a wide operational envelope. The Electron/React-based desktop application provides real-time visualization, interactive 3D bioreactor models, and a simulation history module, making it accessible to researchers, engineers, and students. The platform serves as a digital twin that bridges rigorous bioprocess mathematics with intuitive user interaction, providing a cost-effective tool for designing and optimizing sustainable carbon capture and biofuel production systems.

BackgroundDNA polymerase activity assays are required for enzyme quality control in biotechnology and diagnostics, but standard methods rely on specialist reagents, radioactivity and other hazardous materials, or real-time PCR instruments that are not widely accessible in resource-limited settings. This constrains local production of high quality, validated reagents and increases dependence on imported enzymes. MethodsBased on experiences derived from partnerships with scientists in several low and middle-income countries (LMICs) and stakeholder consultations, we adapted a commercial EvaGreen-based fluorometric DNA polymerase activity assay for isothermal operation using minimal equipment. Assay conditions were optimized using Design of Experiments (DOE) methodology, varying temperature, reaction volume, and MgCl2 concentration. To address reagent cost and supply-chain constraints, we developed detailed protocols for in-house synthesis of the off-patent AOAO-12 DNA dye (sold commercially as EvaGreen) and generation of single-stranded DNA templates via asymmetric PCR. ResultsOptimized isothermal assay conditions (40{degrees}C, 7.75 mM MgCl2) reliably quantified activity across multiple DNA polymerase families. In-house synthesized AOAO-12 dye exhibited comparable DNA-binding performance to commercial alternatives (R{superscript 2} = 0.95), reducing costs by more than an order of magnitude when normalized to working concentrations, enabling assay costs of approximately {pound}0.001 per reaction. The assay is effective across multiple polymerases (Bst-LF, OpenVent, Taq, Q5) and is compatible with both plate readers and qByte, a low-cost, open-source fluorometric device. ConclusionsThis stakeholder-informed assay provides an accessible, cost-effective solution for DNA polymerase quality control in resource-limited settings. The combination of optimized commercial protocols and in-house reagent synthesis offers flexibility for different resource contexts, potentially improving access to molecular biology tools globally.

Holographic imaging in microscopy enables label-free quantitative information of biological specimens and has found applications across a wide range of biomedical studies, from cell morphology to particle dynamics; yet its widespread adoption is often limited by the lack of accessible and standardized analysis software. We present HoloBio, an open-source, Python-based graphical user interface developed to address this issue. This software offers two primary operational modes: a Real-Time mode that enables live processing of holograms at video frame rates, and an Offline mode designed for post-processing previously recorded holograms. HoloBio is compatible with holograms recorded using both lens-based and lensless systems, supporting off-axis architectures in telecentric and non-telecentric configurations, as well as slightly off-axis and in-line optical setups. The software incorporates tools for cell tracking, phase profiling, thickness estimation, and morphological analysis, including cell counting and object area quantification. HoloBio is designed to be accessible for users without coding expertise, offering a reproducible, high-throughput environment tailored for researchers in biology, biophotonics, and biomedical imaging.

Antimicrobial resistance remains a global existential threat. Given that antimicrobial therapy commonly starts before pathogen identification, rapid and scalable methods capable of determining effective antimicrobial compounds are needed. In this paper, we demonstrate a 2 x 2 array of parallelised microscopes that uses low numerical aperture (NA=0.25) detection optics and LED excitation to determine bacterial viability based on their fluorescence response to an electrical stimulus. Following a 2-hour incubation, the fluorescent viability readout requires less than one minute. We use K-means clustering to classify pixels in a time lapse sequence of widefield fluorescence images and extract changes seen within bacterial clusters. We demonstrate sufficient sensitivity to measure fluorescence changes after electrical stimulation in a bacterial monolayer. To capture these subtle fluorescence changes at high signal-to-background ratios, we place a limit on the minimum optical density of the bacterial sample. This novel approach is scalable to 96-well formats using a suitable consumable electrode array.

Super-resolution localization microscopy (SMLM) has become a central tool for nanoscale biological research for its high spatial resolution and compatibility with wide-field microscopy. Achieving quantitative SMLM, however, requires homogeneous high-power illumination, nanometric axial stability, and precise multi-channel detection, features typically restricted to high-end commercial instruments or custom solutions in specialized laboratories. The cost of such microscopes and their technical complexity still limit the accessibility of these advanced imaging techniques. Several home-made single molecule microscopes and their submodules have been demonstrated as opensource, highly-customizable, and cost-effective alternatives for their commercial counterparts. Yet, implementation of such systems often requires expert knowledge in optics, electronics, and control system engineering. We introduce Open Blink, a compact open-source TIRF microscope integrating powerful homogeneous quad-line laser illumination, dual-channel detection, and active focus-lock stabilization for quantitative multi-color super-resolution imaging. Open Blink achieves a localization precision below 10 nm in dSTORM, supports a tunable, large field of view from 105 x 105 {micro}m2 up to 257 x 257 {micro}m2, and maintains axial stability over hours, enabling high-throughput super-resolution acquisition. Built with predominantly off-the-shelf components, and full integration into the open-source software {micro}Manager where metadata registration ensures reproducibility, Open Blink offers a low threshold for adoption by easing implementation, use and maintenance. At a substantially reduced cost of approximately 70 000 Euros, among which the high-power laser combiner alone is less than 20 000 euros, Open Blink greatly improves accessibility for laboratories who wish to implement scalable high performance super-resolution microscopy based on single molecules.

The generation of clonal CHO cell lines is foundational to biologics manufacturing; however, labor-intensive cell culture workflows predominate in the field. We created the CLAIRE (Cell Line AI Recognition and Evaluation) tool to streamline end-to-end cell line development by integrating deep-learning image analysis with automated liquid handling. We benchmarked three object detection models for monoclonality verification and found DETR provides superior accuracy (>0.90 F1-score) in identifying single cells. To quantify the outgrowth of cell lines, we evaluated multiple zero-shot SAM2 segmentation models against a feature-based estimation method. Feature-based detection successfully identified diverse cell colony types while less robust performance was observed for SAM2 models, particularly for sparse density colonies. The pre-trained DETR and feature-based detection models were wrapped in a task-focused user interface that outputs cell line hitpick lists compatible with a Lynx LM1800 liquid handler in addition to custom scripts automating cell passaging and sampling. This approach yielded an end-to-end 36 day CLD workflow capable of generating high-titer cell lines for multiple complex antibody structures. Here, we open-access our trained models, user interface, and Lynx automation scripts to provide a modular toolkit useful for clonal cell line engineering projects. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/703387v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1f72e70org.highwire.dtl.DTLVardef@109c54dorg.highwire.dtl.DTLVardef@7867b1org.highwire.dtl.DTLVardef@dfa61e_HPS_FORMAT_FIGEXP M_FIG C_FIG