Slides presented at the BioData World Congress (Cambridge, October 2015).

1. Applications of high-throughput
sequencing (HTS) technologies in
the pharmaceutical industry
Enrico Ferrero, PhD
Computational Biology @ GSK
BioData World Congress
22.10.2015

2. The drug discovery pipeline
New medicine: $1 bn, 15 years
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK
2

3. Challenges in the pharma industry
Time and costs are increasing but success rate is declining
3Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

4. 4
Computational Biology @ GSK
Supporting the drug discovery pipeline
Target Preclinical Clinical Launch
Disease
understanding
Target
discovery
Drug
MOA
Indication
mining
Patient
stratification
Efficacy and
safety
Drug
repositioning
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

5. 5
Where can HTS technologies help more?
Target Preclinical Clinical Launch
Disease
understanding
Target
discovery
Drug
MOA
Indication
mining
Patient
stratification
Efficacy and
safety
Drug
repositioning
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

6. Genomics and high-throughput sequencing
What HTS technologies do we use?
Transcriptomics Epigenomics Regulomics
RNA-seq ChIP-seq DNase-seq BS-seq

7. Disease understanding

8. Disease progression in rheumatoid arthritis
RNA-seq + BS-seq
 Part of the BTCURE research project, in collaboration with the Academisch Medisch Centrum
(Amsterdam, NL).
 Pilot study involving a small number of synovial biopsies from RA patients at different stages and
degrees of severity.
 Samples profiled by RNA-seq and WGBS to identify gene expression and methylation signatures
that could highlight disease progression mechanisms.

9. Differential expression analysis
9
RNA-seq
 Challenges:
 Data-driven identification
of clinical parameters that
are indicative of disease
progression
 Differential expression
analysis with very limited
number of samples and
high variability
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

10. Methylation data generation and processing optimization
BS-seq
10
 Challenges:
 Set up and optimise protocol(s) in the lab
 Big strain on sequencing facilities and computational environment
 Identification of appropriate analytical methods
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

11. Target discovery

12. Genomic responses to viral infection
RNA-seq + DNase-seq
 Part of an ongoing collaboration with the University of Washington Department of Genome
Sciences (Seattle, WA, USA).
 Pilot study with primary cells from healthy volunteers infected with human rhinovirus.
 Samples profiled by RNA-seq and DNase-seq to identify gene expression and regulatory chromatin
responses to viral infection.
 Identification and validation of pathways and targets for respiratory diseases with a strong
infection component.
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

13. Genomic responses to viral infection
DNase-seq
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK
 Challenges:
 Differential analytical
framework for DNase-seq
data
 Interpretation of biological
signal from DNase
hypersensitive sites

14. Drug MOA

15. Neurogenesis-inducing compounds MOA
RNA-seq
 Study to understand the mechanisms of action of two neurogenesis-inducing compounds and
discriminate between the pathways they activate.
 Neural progenitor cells profiled by RNA-seq to identify gene expression responses to the two
compounds.
 Identification of off-target effects and safety risks.
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

16. Neurogenesis-inducing compounds MOA
RNA-seq
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

17. What else?

18. GSK partnerships with academic institutions
Leveraging HTS technologies to improve the target discovery process
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

19. Summary
HTS technologies in the pharma industry
 Making drugs is a very failure-prone business.
 To increase our chances of success, we need to have better understanding of the biology of:
– Our diseases;
– Our targets;
– Our drugs.
 HTS assays such as RNA-seq, DNase-seq, ChIP-seq and WGBS are getting more and more widely
used at GSK to support these activities.
 Partnerships with CTTV and Altius are going to further increase the importance of HTS
technologies throughout the target and drug discovery pipeline.
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK

20. Acknowledgements
 Disease progression in rheumatoid arthritis
(in collaboration with BTCURE and AMC)
– Rab Prinjha (Epinova DPU, GSK)
– Paul-Peter Tak (Immuno-inflammation TA, GSK)
– Danielle Gerlag (Clinical Unit Cambridge, GSK)
– Huw Lewis (Epinova DPU, GSK)
– Erika Cule (Target Sciences, GSK)
– Klio Maratou (Target Sciences, GSK)
– George Royal (Target Sciences, GSK)
 Neurogenesis-inducing compounds MOA
– Hong Lin (Regenerative Medicine DPU, GSK)
– Aaron Chuang (Regenerative Medicine DPU, GSK)
– Julie Holder (Regenerative Medicine DPU, GSK)
– Jing Zhao (Regenerative Medicine DPU, GSK)
– Erika Cule (Target Sciences, GSK)
 Genomic responses to viral infection
(in collaboration with StamLab and UW)
– Edith Hessel (Refractory Respiratory Inflammation DPU,
GSK)
– John Stamatoyannopoulos (StamLab, UW)
– David Michalovich (Refractory Respiratory Inflammation
DPU, GSK)
– Soren Beinke (Refractory Respiratory Inflammation DPU,
GSK)
– Nikolai Belyaev (Refractory Respiratory Inflammation DPU,
GSK)
– Peter Sabo (StamLab, UW)
– Eric Rynes (StamLab, UW)
Applications of HTS technologies in the pharma industry
Enrico Ferrero – Computational Biology @ GSK