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Counting Costs

The colony forming cell (CFC) assay is universally recognised as the gold standard method for evaluating the effects of radiation, chemotherapeutic drugs and other agents on cell viability. Highly sensitive and biologically relevant, the CFC assay has a valuable place in the cancer research and drug development process. The stringent testing afforded by CFC assays can help eliminate late drug failure and evaluate the viability of therapeutic combinations or dosing regimes. All of which can significantly reduce the time and cost associated with pharma discovery and the evaluation of potential new treatment regimes, where modes of action need to be validated accurately against oncology targets.

Capacity Challenge

Manual counting of CFC assays is a major undertaking in terms of resources and time for research facilities of all sizes. Challenging enough in adherent mono-layer twodimensional samples, in recent years the emergence of sphere formation (or tumour sphere) assays – which simulate tissue state replication – has introduced an additional layer of complexity.

These three-dimensional (3D) in vitro culture systems make accurate visual recognition and consistent manual counting even more time-consuming and difficult for observers to achieve. But for laboratories working at the cutting edge of cancer research – where the emphasis on combination treatments for cancers is growing – being able to perform with ease quantitative 3D assays that fully reflect drug and radiation combinations on proliferating tumour cells is a commercial imperative.

The key challenge for contract research organisations (CROs) engaged in undertaking contract assay services, or participating in preclinical research services where 3D assays are the ‘gold standard’, is being able to gear up capacity without sacrificing quality. Moreover, in a world where strategic partnerships and margin management is part and parcel of thriving and surviving, the CRO industry needs to stay adaptable and flexible if it is to capitalise on the exploding demand for outsourced services in niche therapeutic arenas. Automated colony counting offers a way to resolve the capacity and scalability conundrum, making it possible for CROs to cost-effectively participate in today’s fast-evolving research ecosystems.

Commercial Landscape

In recent years, the world of pharma has undergone a metamorphosis. Increasing price and cost pressures, regulatory changes and expiring patents have driven pharma companies to adjust their business models. The past decade alone has seen R&D costs increase by more than 80 per cent worldwide, while new product launches have fallen by 43 per cent (1). All of which has led to a major re-evaluation of the drug discovery approach.

In a bid to stimulate innovation and lower costs, Big Pharma is electing to outsource its R&D functions, while fostering new and highly strategic partnership networks with academia and prominent research centres. It is also putting the spotlight on therapeutic areas where there is an unmet medical need – for example, oncology, speciality care and biologics – and engaging with new open innovation approaches to drug discovery, where the collective expertise of a network of contributors and knowledge sharing is becoming the norm.

This has commercial implications for CROs: participating in this brave new world means delivering capacity, together with output that meets stringent reporting requirements – including those set down by regulators – for sponsors that may be in disparate locations or countries. Additionally, today’s extended collaboration chains mean CROs must be able to seamlessly share data with multiple parties, demonstrating open and transparent communication capabilities.

Therefore, while high volumes of work are potentially out there for the taking, capitalising on this commercial opportunity is only possible if CROs have the capacity and capability to cost-effectively participate and deliver against fast-changing expectations and evolving discovery models.

Rising to the Challenge

Despite the obvious value and utility of CFC assays, they are generally perceived as time-consuming and technically challenging to set up and analyse. Furthermore, manual counting of cell colonies is a laborious task in which consistent objectivity is difficult to achieve.

In an attempt to lower R&D costs and stimulate innovation, new approaches are being employed to gain a better grasp of the pathophysiology of disease and the efficacy of new treatments. This includes greater use of new technologies to ‘virtualise’ the research process, accelerate clinical development and support greater collaboration between industry, academia and the extended research chain.

The concept of computer-aided colony counting is not a new one. Today’s automated colony counting and integrated image analysis systems now offer an efficient and cost-effective alternative to manual counting, putting the analysis capabilities required to undertake today’s highly sophisticated 3D arrays within the reach of CROs – including small and niche research laboratories (see Figure 1).

Sophisticated and robust image-processing algorithms automate the detection, counting and analysis of mammalian cell colonies in Petri dishes, flask and multi-well plates. Using high depth-of-field scanning, colonies can be imaged, processed and characterised in a single integrated hardware/ software platform, eliminating the disruptive requirement for multiple devices at every stage of the process that characterised the early days of automated counting.

Today’s ‘all in one’ dedicated colony counters deliver superior accuracy and precision in comparison to manual observer counting (see Figure 2). Impressive colony detection performance includes resolution of the overlapping colonies challenge, alongside the exact differentiation of colonies from debris or other artefacts. Offering a standardised method for automated CFC analysis, these systems make it possible for research labs to increase throughput and reduce workflow demands, while simultaneously upping the consistency and accuracy of their results.

Extending Capacity and Capability

Today’s intelligent systems also enable operators to set defined colony thresholds for counts – for example, researchers can elect to exclude colonies based on size or colony shape-related parameters, or assign general object detection sensitivity parameters. In addition, they allow researchers to undertake repetitive plate counting of non-adherent colonies without staining cells.

Technological advancements mean single instrument automated systems can also provide extensive analysis parameters that make unique new insights possible, as well as give labs the facility to capture and report additional qualitative and quantitative data. Alongside generating counts, researchers processing colony samples can now collate detailed colony size information in the form of a mean-per-well/dish, histogram distribution, or on an individual colony basis.

This new-found ability to quantitatively measure, say, the effects of anti-cancer therapeutic regimes on absolute colony numbers and colony size, makes it possible for research labs to extend the sensitivity of the colony forming assay and obtain previously ‘hidden’ information relating to colony growth dynamics.

Collaborative Working

Modern automated intelligence-based systems also enable highly sophisticated data capture and export. Full digital image archiving and per-colony raw data exportation means images of colony plates or dishes can be output directly into lab documentation, or saved as a digital raw image that supports the further processing or reprocessing of samples.

Research labs can visually document individual assay findings instantly, submitting these images to multiple teams or external groups for independent validation and/ or independent processing and assessment. Furthermore, the ability to capture, process and export data makes new collaborative research approaches possible – for example, laboratories can submit assay images for rigorous doubleblind tests – and eliminates the challenges inherent in duplicating assay methodology when undertaking parallel, global or large-scale trials.

For instance, labs looking to engage in multi-site research projects now have the capacity to store and reapply defined assay count parameters in order to maximise counting, proportionality and reproducibility. Settings can also be stored and submitted to other teams or personnel – regardless of location – making parallel validation programmes possible or enabling multiple new drug combinations to undergo parallel assessment. In a similar way, reporting (both during and post-trial) becomes a simplified and automated process; statistical distributions and summary data – including colony numbers and attributes – can be instantly exported in a variety of formats.

Extensive Possibilities

The arrival of highly sophisticated in vitro arrays mean research labs can no longer rely on manual analysis when it comes to cost-effectively undertaking the precise study of drug effects in relation to dose and time of exposure. In the area of oncology, the growing number of agents under development and the heavy focus on combination treatments means that volumes of assays utilised in studies are only set to grow. This makes reproducible and easy-to-form quantitative assays that fully reflect drug effect on both colony size and number a must.

Automating the detection, counting and analysis of mammalian cell colonies offers significant benefits to cancer biologists processing tumour colony forming assays – eliminating the risks of subjectivity, bias and human error, increasing speed and accuracy, and delivering unprecedented data archiving and retrieval capabilities.

For CROs under pressure to maximise throughput and the utilisation of facilities and resources – including highly qualified research technicians – today’s intelligence-based imaging systems automate colony counting, delivering significant enhancements in throughput and productivity.

Moreover, these integrated platforms make it easy to capture and distribute findings and/or share parameter settings, enabling labs to easily replicate largescale assays or distribute elements of large research projects. As a result, teams in multiple locations can undertake parallel assays, instantly replicating count parameters or subjecting arrays to sophisticated validation or peer-to-peer review. This gives CROs the capabilities they need to easily engage in open innovation approaches to R&D and drug discovery, and demonstrate added value to the collective network of research contributors.

The new versatility ushers in an era where CROs of all sizes can maximise sponsor funding in the pursuit of outcomes, and forge powerful new value-added relationships. It also delivers additional flexibility – including the ability to employ sensitive new data collection parameters while undertaking industrial scale array counts – yet maintains that all-important grasp on operational margins.

1. Global pharmaceutical industry is in a strategic crisis – business models must be adjusted, Roland Berger Strategy Consultants, 6th January 2013

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Michael Rau, PhD, is Director for Sales and Marketing at Oxford Optronix. Following a doctorate on the molecular biology of mammalian cell gene expression, awarded at the University of Sussex, Brighton, in 1996, Michael initially pursued an academic pathway with a three-year post-doctoral stint at a human virology research lab in Lyon, France. He joined Oxford Optronix as a Product Specialist in 1999, a time of rapid expansion for the company following the launch of the market’s first dedicated fluorescence lifetimebased, fibre-optic tissue oxygen monitor, the OxyLite™. Michael has an in-depth technical understanding of the company’s products and their application with all sales team members.
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