Productivity & Speed Calculator

See the numbers as a

The Exclusivity Equation

Every Day Counts... to patients, employees, and shareholders

A 20-year patent. Development consumes most of it; what remains is the window in which an asset earns back the cost of reaching patients. Because the expiry date is fixed, reaching the market sooner pays back across every stakeholder — sooner access for patients, capacity returned to teams, and value to shareholders.

Patent filed Patent expires

Year 0 Year 5 Year 10 Year 15 Year 20

Discovery

Preclinical

Clinical (Phase I–III)

Regulatory review

Days accelerated

Commercial exclusivity

Levers

Development timeline 12 years

Days accelerated 90 days

Assumptions · set by audience, adjustable

Peak annual revenue $2.0B

Discount rate 9.0%

Annual therapy cost per patient $40k

More time at peak before a fixed LOE Baseline Accelerated

8.0 years of commercial exclusivity remain after launch — and an earlier launch pays back across all three:

Patients

12,329

patient-years of earlier access

~50,000 patients treated at peak

Employees

29.6

FTE-years of capacity redeployed

to the next program, sooner

Shareholders

$396M

present value of reaching the market sooner

In plain terms: reaching the market sooner doesn't move your patent expiry, so every day earlier is one more day selling at full price before generics arrive — a longer stretch at peak, and more total sales over the product's life. The curve ramps to peak over the years-to-peak assumption, holds peak until loss of exclusivity (LOE), then erodes over the post-LOE decline period to a residual generic-era floor — not to zero. Because the LOE date is fixed and that post-LOE tail is the same whether or not you accelerate, the value of speed lives entirely in the exclusive window; shareholder value is the present value, at launch, of that net-new selling time. Patient access scales the treated population by the time gained; employee capacity scales the core team by the time gained. Directional approximations intended to size order of magnitude, not forecast precise outcomes.

The Productivity Equation

Productivity is output per unit of input.

We don't change the odds a molecule succeeds — that's biology. We change how much throughput an organization gets and what it costs to get there. Productivity moves when output rises or input falls, and both are within reach.

What we don't change — the odds

~1 in 10 clinical candidates ever reaches approval — the probability a molecule succeeds is biology, not process. Everything below is what we move.

Levers — what we move

Throughput uplift (speed-driven) +20%

Direct cost reduction (vendor & process) −15%

Earlier kill decisions (spend less on programs that won't make it) −10%

Assumptions · set by audience, adjustable

Annual program budget $400M

Baseline cost per program $30M

Productivity — output per unit input

1.57×

vs. today's baseline of 1.00×

the same organization, advancing more for less — without touching the underlying success rate

Same spend → more output

+7.6

additional programs advanced per year

Same output → lower cost

$145M

saved per year at the original output

The moonshot — a new playbook for the industry

At this productivity, the industry's current effort — roughly $276B of R&D and ~50 novel medicines a year — could instead deliver +28 more new medicines to patients every year, or redeploy ~$100B of R&D capacity toward the next breakthrough.