Novel computational approaches to discover medicines
Submitting InstitutionNewcastle University
Unit of AssessmentComputer Science and Informatics
Summary Impact TypeTechnological
Research Subject Area(s)
Information and Computing Sciences: Computation Theory and Mathematics, Information Systems
Summary of the impact
New computational analysis methods have been developed to make drug
discovery and toxicological analysis much more efficient. These methods
have been patented (UK, EU, US) and are employed in e-Therapeutics Plc, a
computational drug discovery spin-off company of the University. The
company, introduced to the Alternative Investment Market of the London
Stock Exchange in 2007, is now the eighth largest company (by market
capitalisation - £92.7M (26/6/2013)) in the pharma/biotech sector. The
underlying technologies derive from network analysis and workflow research
at the University. The company has an anti-cancer drug (ETS2101) in phase
I clinical trials in the UK and the US, and an anti-depression drug
(ETS6103) planned to enter phase IIb clinical trial shortly. The
beneficiaries of this research are e- Therapeutics directly, other drug
companies, and ultimately patients.
The case study rests on contributions to network analysis and
application led by Peter Andras, and to workflow development
led by Anil Wipat. Through collaboration with the Faculty of Medical
Sciences at Newcastle University, the research was applied to the field of
network pharmacology. The key computer science researchers are
given below. Andras and Wipat are the lead authors on the respective
Andras, P. (Lecturer/Reader in Complex Systems: 2002-present)
Idowu, O. C. (2003-2005), Lynden, S. J. (2003-2004) &
Periorellis, P. (2000-2004)
Wipat, A. (Lecturer/Reader/Professor of Integrative Bioinformatics:
Lee, P. A. (Professor/ Emeritus Professor, Computing Science:
Lord, P. (Lecturer, Computing Science: 2005 - present)
Wilkinson, D. (Lecturer/ Senior Lecturer/ Professor of Stochastic
Modelling: 1996 - present)
Flanagan, K. (2006-present); Pocock, M. (2005-2010); Sun, Y.
(2003-2006); Wiele, J. (2009-2011); Worthington, J. T. (2005-2006)
Complex networks, whether biological or artificial, can be classified on
the basis of their structure which is important as it can influence the
robustness of the underlying system (one important aspect, for example, is
the pattern of distribution of connections between nodes).The networks
that control processes in health and disease are scale-free networks most
of whose nodes can be bypassed but with a few nodes that receive many
connections and make the whole network vulnerable when they are disrupted.
Within the eXSys project [G1], Andras, working with colleagues,
developed and applied algorithms to analyse the structure of the network
of protein interactions of parasitic bacteria and healthy and diseased
host cells [P1, P2, P4]. The algorithms were applied to the identification
of known protein targets of antibiotics but in the context of their
involvement in key structural elements of the graphs that represent
bacterial cells as protein interaction networks (e.g. penicillin-binding
proteins as bottlenecks, ribosomal proteins as hubs). Further algorithms
are then used to identify an optimal set of points to target and disrupt
the disease process. Finally, an existing drug candidate that interacts
selectively with the target proteins is chosen. These algorithms are
embodied in a workflow, also developed during the research, to create a
pipeline for candidate evaluation. e-Therapeutics, a university spin-out,
was established to commercialise these developments.
Wipat and colleagues worked with e-Therapeutics under a KTP
project [G2], the MicroBase project [G3] and the SABRE Ondex
project [G4]. Microbase is a high throughput analysis system that exploits
highly parallel grid and cloud environments for complex and computational
intensive bioinformatics tasks. The system was used to automatically carry
out "all-against-all" protein sequence similarity comparisons to help
build the protein interaction networks, and to produce predictions about
likely novel antibiotic targets in bacteria for the discovery of the new
targets. The Microbase system was one of the first bioinformatics
pipelines to facilitate a rapid all-against-all comparison of large
numbers protein sequences on the Grid [P4]. This system was successfully
deployed and the resulting protein sequence similarity data was used to
develop e-Therapeutics networks.
Wipat and colleagues also developed integrated networks for
e-Therapeutics within the Ondex project (http://www.ondex.org/)
from 2008-2009 leading to a joint journal publication [P3]. Multiple data
sources were used to produce individual graphs which were then combined to
produce a complex graph, providing a richer view of a drug, its properties
and its interactions. The Ondex system is one of the few systems that can
perform a full graph-based analysis with sufficient semantic rigour to
allow computational reasoning for new drug targets. Ondex was installed in
the company and its employees trained to use it.
References to the research
[P1] Idowu, O.C., Lynden, S.J., Young, M. P. and Andras, P. (2004). "Bacillus
subtilis Protein Interaction Network Analysis". In Proceedings of
IEEE Computational Systems Bioinformatics Conference, pp. 623-625.
[P2] Periorellis, P., Idowu, O.C., Lynden, S. J., Young, M. P., Andras,
P. (2004). "Dealing with complex networks of protein interactions: A
security measure". In Proceedings of 9th IEEE International
Conference on Engineering of Complex Systems (ICECCS), pp.29-36. (UK
Patent GB 2,411,268;) [*Key ref.]
[P3] Cockell, S. J., Weile, J., Lord, P., Wipat, C., Andriychenko, D.,
Pocock, M., Wilkinson, D., Young, M. P. and Wipat, A. (2010). "An
integrated dataset for in silico drug discovery". Journal of
Integrative Bioinformatics, 7(3): 116. [*Key ref.]
[P4] Sun, Y., Wipat, A., Pocock, M., Lee, P. A., Flanagan, K. and
Worthington, J. T. (2007). "Exploring microbial genome sequences to
identify protein families on the grid". IEEE Transactions on
Information Technology in Biomedicine, 11(4) pp. 435-442. [*Key ref.]
Key Research Grants:
[G1] EPSRC eXSys project, 01/01/2003 - 01/01/2005, £179,680. PI:
Watson, Co-I: Andras, Young
[G2] KTP project, 01/01/2006 - 30/06/2006, £60,000. Andras,
[G3] Development of a Data Base for Microbial Genome Comparison
(MicroBase) [11/3/2003 - 13/5/2007] £166,696. PI: Wipat.
[G4] BBSRC BBS/B/13640, BB/F006039/1 SABRE ONDEX, 01/04/08 -
31/10/11, £625,164. PI: Wipat.
Details of the impact
The productivity of research and development spending by the
pharmaceutical industry has fallen dramatically over recent decades, and
it may be that the existing method of reductionist drug discovery -
identifying one `target' protein and then finding a drug that binds to it
— is not suitable for treating complex diseases such as depression and
Alzheimer's disease. This reduction in output has triggered the
pharmaceutical industry to seek to reposition existing (or
somewhat modified) drugs using a network pharmacology approach [E1].
Industry analysts have commented favourably on this new way of finding
medicines. In addition, new drugs based on new chemistry are extremely
expensive to develop (recent figures from the Office of Health Economics
estimate an average cost of £1.2 billion [E2]), many taking 10-15 years to
reach the market. Most candidates fail before or during clinical trials, a
huge burden for the companies concerned.
The repositioning approach to discovering new treatments aims to
find new uses for drugs already on the market or for drug candidates for
which there is substantial safety data, obviating the requirement for many
of the pre-approval tests required of completely new therapeutic
compounds, since the compound has already been validated as safe for its
original purpose. A number of such compounds have been identified
providentially, but network pharmacology provides a systematic
approach to identify new targets and diseases for existing drugs and to
identify drugs that are more effective when used in combination than when
either is used individually. The research from Newcastle University's
School of Computing Science has been applied to this field and underpins
this case study.
Route to impact
In 2002 Malcolm Young and Peter Andras founded e-Therapeutics (www.etherapeutics.co.uk),
a medicines discovery company spun out from their research at Newcastle
University. The company's new and unique approach, which involves network
pharmacology, is protected by six patents that contain more than 200
separate claims of invention and granted in Europe and the USA [E3].
A key feature of the company's method is that it finds the crucial few
proteins that must be targeted to disrupt the disease process; it
therefore follows that a drug candidate which interacts selectively with
those target proteins must be identified. The company initially sought
candidates from among known molecules, using its approach to identify
those suitable for `repositioning' into the disease in question. Such
molecules often have safety data that can support rapid progress into
clinical trials and typically have well-characterised interactions with
In September 2011 the Wall Street Journal published an article titled "Drugs
that are as smart as our diseases" [E4] in which the limitations of
the old approaches to drug discovery and the merits of e-Therapeutics'
implementation of network pharmacology are described.
Drugs in clinical trials
Two drugs, both re-positioned, are currently being evaluated in clinical
trials. The company's anti-cancer drug candidate, ETS2101, is in phase I
clinical trials [E5] in the US and UK. ETS2101 is dexanabinol, a compound
that was thought to have a neuroprotective function after brain injury,
but that was shown in a phase III trial to be safe but ineffective for
this indication (Maas et al., Lancet Neurology 2006. PMID: 1636102).
Network modelling predicted an anti-apoptotic action. One trial involves
patients with primary or secondary brain cancer (started June 2012; key
data on safety and dosing expected Q4 2013) and the other involves
patients with solid tumours (started September 2012; key data expected Q1
2014) [E5]. By May 2013, a total of 17 patients had been treated in the
two phase I trials. No patient had experienced serious adverse events
related to treatment (although one patient experienced severe fatigue
after dosing and continued on a lower dose). One patient with oesophageal
cancer had experienced an objective anti-tumour response.
The second drug candidate, ETS6103, is a generic drug with an established
safety profile. A controlled phase IIa trial of ETS6103 for an
anti-depressant indication, which ended in January 2009, demonstrated
encouraging results when the drug was compared with a marketed tricyclic
anti-depressant: "significantly and consistently reduced depression
scores in all patients during the 12-week treatment period" [E6]. A
larger phase IIb trial is expected to start shortly [E7].
e-Therapeutics has grown substantially since it was founded in 2002. It
was listed on the Alternative Investment Market (AIM) of the London Stock
Exchange (LSE) in November 2007, and with a market capitalisation of £37.3
million at flotation it has become a significant presence in the UK
marketplace with a current (26/06/2013) valuation of £92.7 million [E8].
In May 2013, e-Therapeutics became the eighth largest company by market
capitalisation in the pharmaceutical / biotechnology sector on the AIM
[E9]. In the context of UK university spin-outs, e-Therapeutics
ranks favourably. The 2010/11 UK Higher Education Business Community and
Interaction Survey showed that there were just over 1000 active spin-outs
in which HEIs had equity stakes that year and that the average external
investment was of the order of £0.7 million per company [E10].
In contrast, e-Therapeutics raised £18 million in February 2011 and
another £40 million in February/March 2013 via share issues [E10]. The
major investors are Invesco (49.8%) and Aviva (16.2%) [E10].
Twenty highly skilled people are employed by e-Therapeutics across two
sites in the UK, the Network Pharmacology Centre in Oxfordshire (opened in
February 2012) and the company's facility in Newcastle. Since 2008,
research and development spending has totalled more than £11.3 million.
Money raised from recent share issues is expected to sustain employment
and high levels of research spending through 2017 [E11].
Young (CEO, e-Therapeutics) has acknowledged the key contributions of
Andras and Wipat, and noted that Newcastle University Research has "positioned
e-Therapeutics as the world leader in the new science of network
pharmacology drug discovery" [E12].
Sources to corroborate the impact
[E1] Hopkins AL (2008). Network pharmacology: the next paradigm in drug
discovery. Nat Chem Biol 4(11):682-90
[E2] Mestre-Ferrandiz, J., Sussex, J. and Towse, A. (2012) The
R&D Cost of a New Medicine. London: Office of Health Economics.
[E3] Patents assigned to e-Therapeutics: EP1968237, EP2028792, EP2157734,
EP2154824; US8301391, US7768942, US7990878. Available from
www.google.com/patents [E5] Wall Street Journal (September 2011):
Drugs that are as smart as our diseases. http://online.wsj.com/article/SB10001424053111904265504576567070931547618.html
[E6] Company update on progress of ETS2101 cancer trials, (2012). http://www.etherapeutics.co.uk/userfiles/file/ets2101_trials_update_dec_2012_final_181212.pdf
[E7] Company-reported results of the completed phase IIa trial of
ETS6103, (2009). http://www.etherapeutics.co.uk/userfiles/file/e-Therapeutics%20antidepressant%20trial%20announcement_FINAL.pdf
[E7] Company plan for phase IIb trial of ETS6103 http://www.etherapeutics.co.uk/index.php?option=com_content&view=article&id=3&Itemid=5
[E8] London Stock Exchange: financial information on e-Therapeutics http://www.londonstockexchange.com/exchange/prices-and-markets/stocks/summary/company-summary.html?fourWayKey=GB00B2823H99GBGBXAIM
[E9] London Stock Exchange: AIM index statistics (May 2013). http://www.londonstockexchange.com/statistics/historic/aim/may-2013.xls
[E10] HEFCE HE-BCI (2010-11). Section B UK sector figures for spin-off
and start-up activity. http://www.hefce.ac.uk/media/hefce/content/pubs/2013/201311/Annex%20A%20Summary%20data%20-%20UK.xls.
[E11] e-Therapeutics annual report and accounts (May 2013). http://www.etherapeutics.co.uk/userfiles/file/e-
[E12] Corroboration from CEO e-Therapeutics