and immunological diseases. Monoclonal antibod- ies are now the fastest growing therapeutic class7,8. Forecasts suggest that this market will be worth approximately $125 billion by 20207,8. Unsurprisingly, many commercial developers are now seeking the most efficient and precise methods of monoclonal antibody identification and genera- tion to meet the growing demand and advance this field of medicine7,8. These types of treatment sup- port a more targeted approach to disease manage- ment, but identification of those rare cells produc- ing the highest quality and/or yield of a specific molecule may require analysis of millions or bil- lions of cells.

Personalised medicine and improving patient care

Single cell analysis may bring hope for many people living with life-threatening or lim- iting diseases, offering a greater degree of precision concerning diagnosis and assess- ment of prognosis, as well as targeted or individualised treatments9. Complex diseases, such as cancers, often develop (and progress) as a result of

multiple genetic and epigenetic changes within individual cells. Single cell analysis can identify specific biomarkers within cellular subsets, allowing focused therapies to be directed accordingly to eradicate diseased cells within specific tissues9. Genetic or epigenetic alterations usually occur during the initial stages of disease development, before symptoms become apparent. Early detection of these changes at the cellular level may enable prompt treatment of disease, before it has progressed and spread, when the chances of treatment success are likely to be much greater and lower (more tolerable) drug doses may be effective. Drug resistance represents another major therapeutic challenge for clinicians

treating complex multidimensional diseases. It is estimated that 90% of available drugs are only truly effective in around 40% of patients10. In 2012, calculations sug- gested that ineffective medicines were costing the US economy alone approximately $350 billion each year10. This problem is exacerbated by the development of acquired resistance in patients undergoing treatment over time as further genetic alterations allow diseased cells to evolve mechanisms of survival in a highly toxic environment11. However, the introduction of extremely sensitive single cell analysis techniques can aid the rapid identification of resistance biomarkers to allow alterna- tive or novel treatments to be explored or identified11. These systems recognise bio- logical targets and/or markers in extremely small clinical samples with an exceptional level of accuracy that traditional diagnostic techniques cannot deliver11. Innovations in this area will facilitate more efficient diagnosis and better prediction

of treatment outcomes as well as greater confidence concerning selection of thera- peutic options12. In addition to the potential benefits for the patient in terms of treatment efficacy and safety, this approach also supports more efficient use of healthcare resources in an increasingly financially-constrained environment.


Optimising analysis: a delicate balance of throughput and sensitivity For single cell analysis to be truly commercially viable, systems and procedures must be optimised to ensure maximum throughput, reliable automa- tion of complex processes and high quality results. This represents a costly technical challenge. Measurement of secretory proteins, such as anti-

bodies, that are released from single cells in a pop- ulation can be difficult as these molecules quickly become lost in the ‘molecular soup’ surrounding the cells. Primary cells (from the human body) can be fragile and require careful handling. Conventional techniques are generally unable to offer the optimal balance of high throughput and sensitivity required for analysis in such cells. Flow cytometry or fluorescence-activated cell

sorting (FACS) techniques offer very high through- put levels but can be harsh on delicate primary cell lines as cell suspensions are usually pressure driven through a flow cell13. Manual techniques such as limiting dilution (used in commercial monoclonal antibody production for decades) and clone pick- ing tend to be less abrasive than flow cytometry but offer relatively inefficient solutions in terms of throughput13. Clone picking typically allows approximately 10,000 cellular tests to be complet- ed over a three-week period. Ongoing frustrations in the biopharmaceutical

industry have led commercial stakeholders to seek fully-automated, integrated systems that provide very high throughput alongside delicate handling of cells with the potential to measure difficult tar- gets, such as secretory proteins. In many cases, industrial laboratories may use up to four different single cell processing systems, each offering a par- tial solution, with samples being passed between systems to obtain an overall result. Commercial partners need one system that delivers on every level; simplifying the process, streamlining resources and cutting down on waste.

The promise of picodroplet microfluidics Microfluidic platforms have provided a welcome solution for single cell separation, isolation and analysis, and this approach is becoming increas- ingly popular within the biopharmaceutical indus- try13,14. Traditional microfluidic platforms com- prise small plastic biochips in which fluids are pumped through channels, each around 1µm in depth14. These systems facilitate automated sam- ple testing and innovations have brought various advances in terms of flow rate regulation, channel numbers and throughputs14. Isolating single cells

Drug Discovery World Summer 2018

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