The Connected Lab: Digital Synergies from Data to Models

Abstract

Many areas of research centre around data; how it is collected, stored, analysed and connected with existing data and ideas. In the changing technological landscape and infrastructure these data interactions are becoming increasingly digital. This thesis considers aspects of the full scope of the research environment from experimental creation and extraction of data through the human and technological interaction with the lab, to the analysis of the resulting data. The work described begins to make clear the synergies enabled by the digitalization of the research pathway.

In the first example, literature sources were carefully analysed and uncertainties exposed and explored to allow creation of high quality anion transporter datasets from which QSAR analysis could be carried out to obtain a predictive model. Within these datasets the effect of compound classification and substituent changes were investigated. In parallel work a closer collaboration between modelling and experimental groups took this area further. While no model was developed covering the whole dataset, transformations in the position of the optimum log P and peak activity were discovered dependent on substituent.

In the second example, interactions with the laboratory were investigated through two different aspects. Firstly though remote experiments that were created for undergraduate teaching, which provided a teaching resource for the physical chemistry practical course. The second developed novel interaction methods for application in the lab environment through the use of smart-assistants and the creation of Talk2Lab. This work sets the scene for a framework that could bring the 21st century technology into the research lab to create the connected lab of the future.

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Identifiers

ORCID for Nicola Knight: orcid.org/0000-0001-8286-3835

ORCID for Jeremy G. Frey: orcid.org/0000-0003-0842-4302

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