Management of Life Science Innovations
Scannel et al. (2012)
While there have been many technological advancements over the last 60 years (like
genome sequencing, high throughput screening and the field of biotechnology) the overall
efficiency of R&D (the number of drugs brought to the market) has decreased. This trend is
called Eroom’s Law (as a reference to the opposite of Moore’s Law). This means that there
is a pattern in decrease of approved drugs per billion dollars over time, which holds for a
halving of amount of approved drugs per billion dollars every 9 years. Scannel et al. provide
four main reasons for Eroom’s law to occur:
- The better than the Beatles problem. Imagine how hard it would be to achieve
commercial success with new pop songs if any new song had to be better than the
Beatles, if the entire Beatles catalogue was available for free, and if people did not
get bored with old Beatles records.
- The cautious regulator. Regulations are getting stricter and stricter, because new
strict rules get introduced for every misstep the industry makes. Stricter rules means
more R&D costs.
- The throw money at it tendency, the tendency to add human and other resources to
R&D.
- The basic research- brute force bias. Overestimates the advancements in basic
research.
Symptoms:
- Narrow clinical search: Change in mindset from looking at all biologically active
compounds looking for potential uses to searching for a specific molecule which
would work against a certain disease agent.
- Big clinical trial: number of participants of clinical trials has increased quite a lot.
Multiple clinical trials: every disease indication has a certain amount of existing
therapies, and since this has increased a lot some new drugs have to be compared
to multiple (sometimes dozens) other drugs in multiple clinical trials.
- Long cycle: used to be 4-5 years, can be 9-15 years now.
Reorganization of R&D
- Smaller vs larger R&D units
- Outsourcing R&D to lower-cost countries
- Introduce management metrics
- Making scientists more entrepreneurial
Quick-kill strategies: trying to stop unsuccessful projects as soon as possible
Obstacles:
- progression-seeking behaviour
- the language of failure
- Lack of assay specificity
- insufficient numbers of alternative projects
, Mergers do not necessarily mean that the acquiring company spends more on R&D after the
merger, so they are not better for the industry in general.
Big companies
Large in-house R&D skills and resources
Relate to external R&D (public science, biotech companies)
Organize in-house R&D (different models, compartmentalization and protected spaces,
exploration vs exploitation)
Originator of innovation is often not the company that markets the innovation.
Rise of biotech
3 generations:
Metcalfe 2005
Co-evolution in medical innovation of clinical knowledge and technological capabilities.
‘hero-surgeons’
• conservative community (opinion leaders)
• emergence of new community
• trial-and-error learning
• codification (papers, patents)
• entrance of firms
• medical profession remain important in diffusion
(peer review; standards)
• development of regulations (creates trust in field)
• network of consumer activists
Biotech business models:
Scannel et al. (2012)
While there have been many technological advancements over the last 60 years (like
genome sequencing, high throughput screening and the field of biotechnology) the overall
efficiency of R&D (the number of drugs brought to the market) has decreased. This trend is
called Eroom’s Law (as a reference to the opposite of Moore’s Law). This means that there
is a pattern in decrease of approved drugs per billion dollars over time, which holds for a
halving of amount of approved drugs per billion dollars every 9 years. Scannel et al. provide
four main reasons for Eroom’s law to occur:
- The better than the Beatles problem. Imagine how hard it would be to achieve
commercial success with new pop songs if any new song had to be better than the
Beatles, if the entire Beatles catalogue was available for free, and if people did not
get bored with old Beatles records.
- The cautious regulator. Regulations are getting stricter and stricter, because new
strict rules get introduced for every misstep the industry makes. Stricter rules means
more R&D costs.
- The throw money at it tendency, the tendency to add human and other resources to
R&D.
- The basic research- brute force bias. Overestimates the advancements in basic
research.
Symptoms:
- Narrow clinical search: Change in mindset from looking at all biologically active
compounds looking for potential uses to searching for a specific molecule which
would work against a certain disease agent.
- Big clinical trial: number of participants of clinical trials has increased quite a lot.
Multiple clinical trials: every disease indication has a certain amount of existing
therapies, and since this has increased a lot some new drugs have to be compared
to multiple (sometimes dozens) other drugs in multiple clinical trials.
- Long cycle: used to be 4-5 years, can be 9-15 years now.
Reorganization of R&D
- Smaller vs larger R&D units
- Outsourcing R&D to lower-cost countries
- Introduce management metrics
- Making scientists more entrepreneurial
Quick-kill strategies: trying to stop unsuccessful projects as soon as possible
Obstacles:
- progression-seeking behaviour
- the language of failure
- Lack of assay specificity
- insufficient numbers of alternative projects
, Mergers do not necessarily mean that the acquiring company spends more on R&D after the
merger, so they are not better for the industry in general.
Big companies
Large in-house R&D skills and resources
Relate to external R&D (public science, biotech companies)
Organize in-house R&D (different models, compartmentalization and protected spaces,
exploration vs exploitation)
Originator of innovation is often not the company that markets the innovation.
Rise of biotech
3 generations:
Metcalfe 2005
Co-evolution in medical innovation of clinical knowledge and technological capabilities.
‘hero-surgeons’
• conservative community (opinion leaders)
• emergence of new community
• trial-and-error learning
• codification (papers, patents)
• entrance of firms
• medical profession remain important in diffusion
(peer review; standards)
• development of regulations (creates trust in field)
• network of consumer activists
Biotech business models:
