Year: 2015-16

Company: Eli Lilly

Liaison(s): John Stafford Matthew Walworth

Eli Lilly is a global pharmaceutical company
headquartered in Indianapolis, Indiana. The company
was founded in 1876 and operates in over 50 countries
with approximately 41,000 associates worldwide. Eli
Lilly earned revenues of $19.6B in 2014, with $2.39B
in operating income from recurring activities. With
over 70 therapeutic agents in its pipeline, Eli Lilly’s
R&D team strives to deliver innovative solutions in five
main disease areas: diabetes, oncology, immunological
diseases, neuroscience and pain, and cardiovascular
Electronic laboratory notebooks (ELN) serve to
streamline R&D activities. Eli Lilly currently utilizes
an ELN but the tool is inefficient and lacks capabilities.
The scientists undergo a laborious and time-
consuming process of moving, reviewing, annotating
and summarizing the data as it is documented into
the notebook. Moreover, this manual process is not
reproducible and decreases productivity. The new
OneLab ELN will act as a central repository for
capturing, analyzing, and storing multiple forms of
data that can be easily shared and accessed by a global
network of all Eli Lilly scientists. It aims to address
a variety of data capture needs across laboratories
all over the globe, and to provide automation and
customizability to improve efficiency.
To identify user needs, the Eli Lilly TMP team visited
the Lilly Research Labs and conducted interviews
with over 30 scientists from four different research
areas. The results of the onsite interviews revealed
six functional areas that address user needs common
to all research areas. These were incorporated into
the ELN and include video analysis, data analysis,
machine learning, voice-to-text, storage, and an
interface. The team worked towards providing viable
solutions to these functional areas by compiling a
list of over 50 potential technologies (products and
services) that can be integrated within the Eli Lilly
ELN. Then, the team performed secondary research
on these technologies. Primary research on the most
promising technologies followed; this included
interviewing key opinion leaders and subject matter
experts, and also demonstrating the technologies. The
final recommended technologies were used to construct
a proof-of-concept ELN that would streamline the
workflow of how scientists collect and share data
under one seamlessly-integrated, user-friendly interface.