Group 1

Shalina Bhatia 119 Arun Ravindran 138 Suman Kumar Saha 245

Anto Abraham 073 Arpit Rastogi 077 Ritesh Jain 112 Sandeep Tripathy 114

Shikha Gupta 300 Suja Barua 306 Suseendran 308 Vishal Gagrai 316

Case facts

Environmental analysis

Competitive landscape

New Product development process

Resistance to new technology – human factors

Evaluation of options

Recommendations

World’s largest and most profitable industry with a revenue of around 250 billion US$

Capital intensive industry around 15-20% of sales spent on R&D

Long time to market : 14.8 years 3 out of 10 drugs Profitable , Price slashed after expiry of patent Shortening lead time became priority

Acquisitions of innovative and cost effective firms

Importance of genetic engineering, combinatorial chemistry and high-throughput screening

Founded in 1876 by Colonel Eli Lilly and leader in industry for 120 years

Offices in 150 countries, Revenue of $5.7 billion From Antibiotics to genetically engineered products Dwindling pipeline of products, hence a fall in market value 1993 Tobias, CEO, sold medical device and diagnostic unit to

focus on core business More Research focus Acquired Sphinx Pharmaceuticals

Increase the synthesizing capability by 50 times

Would increase capacity to screen compounds by 8 times

Synthetic chemistry

• More powerful than the naturally occurring compounds

• Cumbersome process

Combinatorial chemistry

• A library of related molecules was created with base remaining the same

• Various combination of compounds tried clinically

High-throughput screening

• Testing by Robots

• The fit was defined through a color change or any other receptor

Around 10% of the lifetime years lost are due to CNS Lilly was spending around 1billion US$ on research for

diseases like insomnia, migraine, clinical depression etcetera CNS market was around 11.1 billion US$ 80 % from G7

nations Success of serotonin based Prozac Focus on Serotonin based drug for Migraine Imitrex for Migraine

Time to market

• Delay causes loss in revenue and also Strategic loss

Diversity of Leads

• The best compounds should be taken forward

Traditional or combinatorial chemistry

• Quicker but problematic

• Delay Vs Passing rate

• Pass the 3 phases of US FDA Regulatory factors

• Combinatorial chemistry Technological

factors

• Aging US population and its diseases Demographical

factors

• Prices of drugs were exorbitant

• Cost effective techniques and related acquisitions

Pricing/Cost pressures

• Strong early mover advantage Early entrant

• Eli Lilly abided by the regulatory rules Regulatory

• Combinatorial chemistry

• Acquisition of Sphinx

Technological factors

• Focus on depression, hypertension, cholesterol , CNS disorders

Demographic factors

• Focus to develop drug quickly at a lower cost

• Concentrated on its core competency

Pricing / Cost pressures

• Focus on the side effects and drawback Imitrex

• Combichem to quicken process Early Entrant

Comparison of balance sheet summaries

Company

Sales in $ Mn

R & D in $ Mn

R &D as % of Sales EBIT

Net Income

NI as a % of Sales

RoE in %

RoA in %

Bayer 28023 2050 7.32 2430 1271 4.54 11.9 4.7

Ciba-Geigy 16171 1578 9.76 2232 1403 8.68 12 6.1

J & J 15734 1278 8.12 2867 2006 12.75 28.2 12.8

Merck & Co 14970 1231 8.22 4633 2997 20.02 26.9 13.7

Bristol-Myers Squibb 11984 1108 9.25 2638 1842 15.37 32.3 14.3

Sandoz 11639 1199 10.30 NA 1272 10.93 20.7 8.9

Hoffman-La Roche 10816 1710 15.81 3110 2098 19.40 17 8.6

SmithKlime Beecham 9933 976 9.83 1213 110 1.11 12.4 0.9

Abbott Lab 9156 964 10.53 2228 1517 16.57 37.5 17.8

Average 11.23 13.32 22.96 9.87

For large companies, R & D expense as a proportion of sales is less

Having high R & D expense ( both absolute and relative ) does not assure superior returns

Company Sales in $ Mn

R & D in $ Mn

R &D as % of Sales EBIT

Net Income

NI as a % of Sales

RoE in %

RoA in %

American Home Products 8966 817 9.11 2145 1528 17.04 35.9 7.1 Glaxo 8484 1287 15.17 2826 1955 23.04 25.2 16.1 Pfizer 8281 1139 13.75 2003 1298 15.67 30 11.7 Hoechst Celanese 7794 313 4.02 -55 186 2.39 5.9 2.3 Tekeda Chemical 7778 677 8.70 1124 518 6.66 7.7 4.5 Eli Lilly 5712 897 15.70 1828 1286 22.51 22.1 8.2 Sankyo CO 5575 477 8.56 887 395 7.09 11.3 5.8 Schering Plough 4657 620 13.31 1281 922 19.80 58.6 21.3 Rhone-Poulenc Rorer 4175 611 14.63 547 341 8.17 21 7.6 Wellcome Plc-ADS 3096 542 17.51 1098 632 20.41 22.1 14.4 Maion Merrell Dow 3060 462 15.10 632 438 14.31 20.5 10.6

Average 11.23 13.32 22.96 9.87

Eli Lilly : High R & D to Sales ratio as well as Net Profit Margin, Average RoE and less than average RoA

1994 Rank

1993 Rank Product Marketer Marketer's RoE

1 1 Zantac Glaxo-Wellcome Glaxo : 25.2% Wellcome : 22.1%

2 2 Vasotec Merck 26.90% 3 4 Prilosec Astra & Merck Astra : NA Merck : 26.9%

4 10 Zovirax Glaxo-Wellcome Glaxo : 25.2% Wellcome : 22.1%

5 6 Prozac Eli Lilly 22.10%

6 3 Capoten Bristol-Myers Squibb 32.30%

7 5 Mevacor Merck 26.90%

8 8 Adalat Line Bayer 11.90%

Average RoE = 22.96%

No direct correlation between R & D expense and superior returns or Profit Margins

Many Large firms don’t have products at the top Past and current investments may result in future ‘Hit’s Why low RoE and RoA for many large firms ?

Iterative Processes and serendipity

Probability of success : 30%

Long duration before product launch

Few extremely successful products

A critique

Basic Research

• Basic Research for 2 years

• Iterative process for ‘Lead’ compound

Preclinical Screening

• 3 years

• Animal testing to ensure drug safety

Human Clinical Trials

• 6 years

• Most stringent and time consuming : 3 phases

FDA Review

• 2-3 years

• 10% of drugs entering clinical trials reach market

Only phase that can be quickened

Quick ‘LEAD’

High throughput screening : Biologically test compounds from

all family of derivatives by Robots

Variations in molecular structures to create a

large pool of compounds

Iterative process in Traditional Chemistry

ADVANTAGES

Multiple derivatives at one go, so less time-to-market

Less expensive First mover advantage

DISADVANTAGES

Chosen compound may not be the best one

Highly risky Not widely used, unproven Not 100% pure compounds

as compared to conventional methods

Employee resistance : can be mitigated

ADVENT

Latent/unarticulated needs : Need Seekers

Combine off-the-shelf products : Collaborative innovation

Non-iterative, parallel process

Minimal R & D and time to market

Kloss had unlimited power More collaboration across

teams

ELI LILLY

Unmet Needs : Need seeker

Build/Acquire capabilities : Internal innovation

Iterative innovation process Extensive R & D and time to

market ( Industry specific ) PTAC had power, not

individuals Less collaboration ( non-

parallel processes )

Human Factors Influences

Honest disbelief in the dramatic but

substantiated claims of the new process

Maintenance of the existing society with

which people identify themselves

Protection of existing devices and

instruments with which they identified

themselves

Skepticism : Voodoo Science

• Combichem generated compounds that were only 80-90 % pure

• Unproved Technology: a distraction

• Technology not trustworthy with many unresolved problems

Threat to Jobs

• Robots Vs Traditional Chemists

Identification with Process as opposed to the Product

• Generating a library of millions of compounds could outstrip the capacity of a screen capable of processing only a thousand compounds

Prob Cost

NPV(Billion $) Worst Best ER

Normal Launch as per industry sales $3.89 8.88 11.12 -0.23 0.13595

Normal launch with increcase mkt $12.04 8.88 11.12 -0.23 0.859659

Year delay $3.74 10.40 13.60 -0.23 0.182918

Two Year delay $3.54 12.12 17.88 -0.23 0.226318

Second Mover $1.77 12.1194 17.8806 -0.23 0.012162

As per computaion in the case $0.77 8.88 11.12 -0.23 -0.14085

Should wait for optimal compound

Negative expected return with current strategy

Increased probability of success with delay

• Late release (no completion)

• Late release (second mover)

Combinatorial Chemistry

• No Visible effect for launch of Migraine Drug

• Learning will be useful for future products

• Cost optimization

http://www.nytimes.com/1999/03/20/business/lilly-to-stop-developing-migraine-drug.html http://en.wikipedia.org/wiki/LY-334,370