Building a Smart Laboratory 2018


with the transition from paper to digital, which includes both the transfer of paper-based processes to ‘glass’ and the identification and adoption of information and process standards to harmonise data exchange.


Think exponential


Traditional mainstream LIMS will face challenges. LIMS has been a brilliant tool to manage predictable, repeatable planned sample, test and study data flows, creating structured data generated by laboratories. In R&D environments, unpredictable workflows creating massive amounts of unstructured data showed that current LIMS systems lack the capability effectively to manage this throughput. ELNs are great tools to capture and share complex scientific experiments, while an underlying scientific data management system (SDMS) is used to manage large volumes of data seamlessly.


Data consumer vs data creator examples


For the researcher, the ability to record data, make observations, describe procedures, include images, drawings and diagrams and collaborate with others to find chemical compounds, biological structures – without any limitation – requires a flexible user interface. For the QA/QC analyst or operator, the requirements for an integrated laboratory are quite different. A simple, natural language-based platform to ensure that proper procedures are followed will be well received. Product innovation and formulators will


need the capability to mine data across projects, analytical methods or formulations to create valuable insights. Transforming unstructured scientific experimental data into a structured equivalent will be mandatory to perform these tasks.


Organisations with a strong consumer


marketing focus deal with data mining techniques providing clear pictures of products sold, price, competition and customer demographics.


New trends


Te power of life cycle process improvement Te scientist is no longer in the laboratory, but integrated in the overall quality process. Quality should be built into the design throughout the specification, design, and verification process. Performance metrics on non-conformance tracking are mandated and monitored by regulatory authorities. Integrating laboratory systems will add significant value by decreasing non-conformance.


New budgeting and licensing models Managing operating budgets will be redefined in the next decade. Te days of purchasing soſtware as a capital investment (CAPEX) are


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An introduction to: Building a Smart Laboratory 2018


changing to a new model based upon a ‘pay-as- you-go’ or philosophy (OPEX). CRM applications such as SalesForce.com started this business model in the traditional enterprise business soſtware segment. Popular applications such as Photoshop, Microsoſt Office 365 and Amazon are following these trends rapidly. It is expected that scientific soſtware suppliers will be forced to follow the same model in the years to come. Community collaboration and social networking is changing the value of traditional vendor help desks.


Reduce and simplify workflow complexities Te need to simplify our scientific processes will have a significant impact on reducing data integrity challenges. For example, balance and titrator instruments may store approved and pre-validated methods and industry best practice workflows in their firmware.


Adopt and use industry standards and processes Initiatives such as the Allotrope Foundation are working hard to apply common standards. Te Allotrope Foundation is an international not-for- profit association of biotech and pharmaceutical companies, building a common laboratory information framework for an interoperable means of generating, storing, retrieving, transmitting, analysing and archiving laboratory data and higher-level business objects.


Consolidation and harmonisation of systems


Most laboratories already depend on an informatics hub comprising one or more of the major tools: laboratory information management systems (LIMS); electronic laboratory notebooks (ELN); scientific data management systems (SDMS); chromatography data-handling systems (CDS) and laboratory execution systems (LES). Te trend over recent years has been towards convergence, applying best practice industry standard processes to harmonise multisite deployments. Cost reduction to interface harmonised processes to ERP (SAP), MES and CAPA results in lower maintenance and validation costs with a significant overall higher system availability for end-users.


Mobile computing


While many other industries are implementing modern tools to connect equipment wirelessly, many laboratories still write scientific results on a piece of paper, or re-type them into a computer or tablet. Many modern ELN and LES systems allow electronic connection to a (wireless) network. However, to integrate simple instruments like a pH balance, titration and Karl-Fischer instruments to mobile devices, a simpler approach is required in order to achieve


mainstream adoption. Te acceptance of tablets and mobile devices will expand exponentially in the laboratory. Laboratories will need to manage the


challenges presented by new consumers of scientific data outside traditional laboratory operations. Non-invasive, end-to-end strategies will connect science to operational excellence. Technology will be critical, but our ability to change our mind-set to enable this cross- functional collaboration will be the real challenge. n


Adapting to change


Much of the change that drives new processes or methods in the laboratory is based on regulation from that aims to more tightly control the way in which data is collected, stored and handled. Many laboratory users will be aware


of previous regulations such as Title 21 CFR Part 11, part of Title 21 of the Code of Federal Regulations that establishes the United States Food and Drug Administration (FDA) regulations on electronic records and electronic signatures (ERES).[1] Part 11, of the document, as it is


commonly called, defines the criteria under which electronic records and electronic signatures are considered trustworthy and equivalent to paper records. However new regulation around General


Data Protection Regulation (GDPR) and data integrity are new standards that laboratory users must now familiarise themselves with. For many users GDPR will not be applicable as it only relates patient data or companies that hold data of EU citizens. However, if in a clinical setting GDPR could have a huge effect on the way that you store patient data. [2] In addition to GDPR lab managers must


also familiarise themselves with pending regulation on Data Integrity (DI) which hopes to improve completeness, consistency, and accuracy of data recorded by laboratories [3]


. In simple terms this means


abiding by principles such as ALCOA (attributable, legible, contemporaneous, original, and accurate). However it is advised that lab managers and users explore the ramifications of this new regulation to see how it might affect daily workflows.


References


1. https://www.fda.gov/regulatoryinformation guidances/ucm125067.htm


2. https://www.ncbi.nlm.nih.gov/pmc/articles PMC5346164


3. https://www.fda.gov/downloads/drugs/guidances ucm495891.pdf


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