PHARMACEUTICALS

PADMAKAR GUNTUR VAMSIDHAR M

KRISHNA MUTTOJUPANKURI JAINSWATI BAJAJ

HIMA BINDHU

InsightsWithin R&D there is need of superior innovation and

lower costs which is achieved through: A comprehensive understanding of how the human

body works at the molecular level. A much better grasp of the killer-effects from

consumptions of drugs including side effects and intricacies caused

Greater collaboration between the industry, academia, the regulators, governments and healthcare providers.

Insights….

Business Problem-1• It is acknowledged that the pharmaceuticals industry has enormous

expenditure in building a successful molecular composition in a time frame. R&D activity which is extensively outsourced predominantly occupies a great share of the incurred cost.

Analytical consultation• Bench marking of the outsourced R&D

– The R&D divisions per phase , per drug, per disease are benchmarked to indentify the best and the worst performing units resulting in the

significant reduction of the outsourcing costs.– The analytical solution provides atleast a 40 %

saving

average R&D cost per unit Average cost after bench marking

0102030405060708090

100

(in m

illio

ns)

Cost saved is 40%

Cost model

average Estimated cost for a molecule composition 1 Billion $

average Number of phases 10average number of R&D units per phase 10

average cost /R&D unit 10 M$expected savings if the 4 least performing units are stopped funding 40 M$

Estimated cost for benchmarking 0.3 M$ Projected price for providing this analysis 4 M$

Technical analysis For Benchmark

• DATA TYPE: Disease(cat), Drug(cat), Costs Incurred(neu),Cost, Time Period(neu),

Number of Failures before successful experiment(neu), Team Size(neu), Successful/Failure Experiment (cat), R&D Firm(cat), R&D Firm Demographics(cat), R&D Firm Size(neu), etc

• DATA VOLUME: 20 to 40 input and output parameters

• IMPLEMENTATION: Quantify the level/positioning of each R&D Firm and identify top most firms for outsourcing.

• PROBLEM CLASS: Linear Optimization

• TECHNIQUE: DEA

Business Problem-2 The formula of the created molecular composition many a time goes to

trash as the usage results many a side effect apart the suffering of patent uniqueness.

Pharma Killer effects and patent tool (PAT -- Pharma analytic tool)

• The software tool that we would be providing would explain the pharma scientist the possible side effects and its intensity for a molecular composition.

• It also validates the formula for its uniqueness by checking with the patent database

• Maintenance and service is entertained for this tool.

• Based on the data generation, the tool would upgrade itself and provide the updated results.

Cost model for PAT

Domain understanding 1 month

Collecting and processing of the data 3 months

Analysis and training 3 months

Testing 2 months

Integration 2 months

Design 1 months

Cost per hour 80 $Cost of the tool PAT 0.6 M $

Support per hour 60 $

Technical analysis for PAT• DATA TYPE: Disease(cat), Drug(cat), Molecule Composition(cat),Costs Incurred(neu), Time

Period(neu), Number of Failures before successful experiment(neu), Side effects and/or Intricacies if any (cat)

• DATA VOLUME: One Record for each type of molecule composition. Patent database.

• IMPLEMENTATION: Given the molecule composition of a drug, to classify whether Side effects and/or Intricacies is caused or not. And if caused then which out of given Side effects and/or Intricacies categories. Patent search,

• ERROR MEASURE: RECALL

• PROBLEM CLASS: CLASSIFICATION

• TECHNIQUE: DECISION TREE,NAÏVE BAYES, RANDOM FOREST, Page ranking, K-NN using HADOOP

PAT Framework

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Projected

The tool saves the 40 % time wastage in killer experiments and patent findings.

40%

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