1 The problem as it stands Outline problems associated with the existing methods of bringing New Chemical Entities (NCEs) to market Outline where attrition rates are highest and where significant savings need to be made Outline how this has been achieved in other industries such as aerospace and aviation Outline examples in the scientific literature of achievements modelling biological molecules and their interaction with human proteins ranging from coarse-grained models to molecular dynamics right up to ab initio quantum mechanics Estimates in 2004 put the costs of discovering and developing a drug up to the order of US$ 900 million yet only 3 in 10 drugs that make it to market recover the original investment made in them

2 A PricewaterhouseCoopers study form 2008 identified some key areas in which the pharma industry could become more innnovative thus reducing its R&D costs These included developing a comprehensive understanding of how the human body works at the molecular level along with a much greater use of new technologies in order to “virtualise” the research process thereby accelerating clinical development Source: FDA CDER, PhRMA and PricewaterhouseCoopers analysis The problem as it stands The virtual vermin * implementation, allowing researchers studying Type I diabetes to simulate the effects of new medicines including different dosing levels and regimens on different therapeutic targets * Developed by The American Diabetes Association and US Biopharma company Entelos

3 Current Ideas for types of modelling Bioinformatics creating the “virtual man” but requiring a significant global effort comparable to that of the Human Genome Project Parametric empirical models based on existing experimental data such as the virtual vermin, or the creation of 3D images from experimental data to enable closer scrutiny. 3 A study conducted at the Supercomputing Facility for Bioinformatics & Computational Biology Indian Institute of Technology, Delhi in 2005 concluded that in silico intervention in drug discovery can save up to ~ 15% of time and cost which could be significant for life threatening diseases.

4 The Current Research Process Source: PricewaterhouseCoopers

5 Current examples of in silico pharma research The Step Consortium - investigating the human body as a single complex system The Living Human Project - an in silico model of the human musculoskeletal apparatus The Physiome Project - a computational framework toward understanding the integrative function of cells, organs and organisms Model Trial - Entelos have developed their virtual research laboratory 5

6 Airline design in silico Elimination of > 3000 assembly interfaces, without any physical prototyping 90% reduction in engineering change requests (6000 to 600) 50% reduction in cycle time for engineering change request 90% reduction in material rework 50x improvement in assembly tolerances for fuselage Boeing invested more than $1 Billion (and insiders say much more) in CAD infrastructure for the design of the Boeing 777. Boeing reaped huge benefits from design automation. The more than 3 million parts were represented in an integrated database that allowed designers to do a complete 3D virtual mock-up of the vehicle. They could investigate assembly interfaces and maintainability using spatial visualizations of the aircraft components to develop integrated parts lists and detailed manufacturing process and layouts to support final assembly. The consequences were dramatic. In comparing with extrapolations from earlier aircraft designs such as those for the 757 and 767, Boeing achieved :

7 Simulations within the Microelectronics Industry Stanford University electrical engineering Professor and former CIS director Bob Dutton recalls that Intel gave him some of the earliest support for his work in the early 1980s on creating semiconductor device and process simulation tools. Ultimately the software his group created, programs like SUPREM and PISCES, became standards for the industry as chips became more complex and simulation tools became indispensable. “Intel provided seed funding for some of this work and they were early adopters of the tools,” Dutton said. “In the ‘80s people were seeing percent savings in their silicon experiments by using simulations to cut down on trial and error.” “In 1995 when Intel introduced the Pentium processor… there was no way to quantitatively measure adhesion,” Dauskardt says. “We developed a method to do that. There is not a single microelectronics company in the world that doesn’t use this technique.” Investment in novel simulation techniques can provide savings by reducing experimental costs and can bring further revenue in the future from widespread use of methods developed

8 Simulation: The Third Pillar of Science Traditional scientific and engineering paradigm: Do theory or paper design. Perform experiments or build system. Limitations: Too difficult -- build large wind tunnels. Too expensive -- build a throw-away passenger jet. Too slow -- wait for climate or galactic evolution. Too dangerous -- weapons, drug design, climate experimentation. Computational science paradigm: Use high performance computer systems to simulate the phenomenon Base on known physical laws and efficient numerical methods.

9 Industries Making Use of Simulation Science Global climate modeling Astrophysical modeling Biology: genomics; protein folding; drug design Computational Chemistry Computational Material Sciences and Nanosciences Engineering Crash simulation Semiconductor design Earthquake and structural modeling Computational fluid dynamics Combustion BusinessFinancial and economic modelingTransaction processing, web services Search enginesDefenseNuclear weapons - - test by simulationsCryptography

10 Economic Advantages of Simulations Airlines: System-wide logistics optimization systems on parallel systems. Savings: approx. $100 million per airline per year. Automotive design: Major automotive companies use large systems (500+ CPUs) for: CAD-CAM, crash testing, structural integrity and aerodynamics. One company has 500+ CPU parallel system. Savings: approx. $1 billion per company per year. Semiconductor industry:Semiconductor firms use large systems (500+ CPUs) fordevice electronics simulation and logic validation Savings: approx. $1 billion per company per year.Securities industry:Savings: approx. $15 billion per year for U.S. home mortgages.

11 Future Potential (?)

Building a Business Case for More in silico Modelling in the Pharmaceutical Industry A. L. Eiden, G. Lever, J. Loh and A. Nicolas CUTEC advisor: P. ZulaicaMedImmune Mentor: B. Agoram

13 FIRST SLIDE - scare tactics, figures, plots AIM: figures, numbers costs, plots AN present: GL

14 SECOND SLIDE - current process, how can be improved Figure of saving from SCF / nature 2009 paper HIGHLIGHTING FILTERING PROCESS JL present: GL

15 STATE OF THE ART - OTHER INDUSTRIES 15 GL present: AE

16 STATE OF THE ART - PHARMA INDUSTRY THEORY, APPLICATIONS, SPECIFIC EXAMPLES AE present: AE

17 2 INDIVIDUAL CASE STUDIES CASES THAT ARE PARTICULARLY SUCCESSFUL VIRTUAL VERMIN, QSAR, ETC ETHICAL IMPLICATIONS OF ANIMAL TESTING ENERGY IMPLICATIONS OF IN SILICO - DESKTOP PC EXAMPLE (QSAR - JL) VMOUSE - AE DESK - GL present: AE

18 IDEAS WE PROPOSE 3 CORE IDEAS 18 GL present: JL

ACADEMICS JL 19 present: JL

IN HOUSE GL 20 present: JL

ACQUISITION AN 21 present: JL

22 BEST ONE FOR INVESTORS / INDIVIDUAL STRENGTHS & WEAK ACQUIRING - REFERRING BACK TO STATE OF THE ART PHARMA COMPANIES SPECIFIC TO MEDIMMUNE METRIC: TIMESCALES, COSTS INVOLVED, OPERATIONS - EASE OF IMPLEMENTATION, CHANCE OF SUCCESS OF RETURN (PROFITS, PATENTS, ACQUIRING: ADV - TIMESCALE 22 AE present: AN

23 FINAL SUMMARY BENEFITS OF IN SILICO IN GENERAL, ANY QUESTIONS ? THINK OF THE ANIMALS... ALL LOOK for cute pictures AN present: AN