The foundation of advances in human healthcare is based on the successful translation of preclinical research based on animal models. The sophistication of genetically engineered models and the analytical tools used to investigate and understand diseases has developed exponentially in recent years. There is great interest and excitement about the role machine learning or AI and predictive analytics can play in further enhancing our insights into variables that lie at the heart of discovering relationships between the drugs and therapies we have targeted and the clinical outcomes we expect them to deliver.
However, in our 21st Century in-vivo research laboratories, we continue to see a reliance on out dated, unreliable and error prone processes and technologies. Scientific rigour is a hit and miss affair: experimental design and execution does not yet consistently meet commonly accepted standards of best practice.
Paper lab notebooks are still common primary sources of research data collection and recording; Excel spreadsheets still dominate as a source of data storage and analysis; identification methods for lab animals still rely on tissue removal and idiosyncratic pattern recognition. The lab of today still runs largely on analogue technologies and lacks data quality assurance procedures to identify sources of error. Many of the key variables effecting the research outcomes are not even recorded. It is no surprise that preclinical research struggles to achieve levels of reproducibility expected in other scientific disciplines. Investment in AI is wasted if you cannot guarantee the authenticity and accuracy of your data.
So, the Preclinical Research Lab of the Future must address the need for scientific rigour, reproducibility (which demands data transparency and availability) and modern standards of best practice in research. That Future Lab has arrived: it marries reliable animal identification with automated experimental data collection; best practice experimental design and planning with secure, auditable chain of custody of the data; and efficiency, accessibility and affordability.
With Somark’s SensaLab platform, say goodbye to paper, data exports to Excel, inconsistent experimental processes and uncertain data authenticity and say hello to the Future Lab, today.