From bench to bedside: the science-to-market pipeline

What we are following: a cancer antibody

A monoclonal antibody (often shortened to "mAb") is a lab-made protein designed to bind a specific target, for example a protein on a cancer cell. Many blockbuster oncology drugs are antibodies. They are large, complex molecules made in living cells, which makes them a biologic (as opposed to a small-molecule drug made by chemistry).

We follow this candidate because antibodies are central to modern oncology and illustrate the pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète → clearly. The stages below apply broadly across drug development.

Stage 1: Discovery and preclinical (roughly 3 to 6 years)

Discovery is target selection and molecule design. Teams screen thousands of candidate antibodies to find ones that bind the target tightly and do the intended job (block a signal, flag the cell for the immune system, or deliver a toxic payload).

Preclinical work tests the lead candidates in cells and animals. Two questions dominate:

• Does it work? (efficacy)
• Is it safe enough to try in humans? (toxicology)

Most candidates die here. A molecule that looked promising may be toxic, unstable, or impossible to manufacture at scale. This stage is comparatively cheap, but it sets up everything downstream.

The gate at the end is a regulatory filing. In the United States, this is an Investigational New Drug (IND) application to the FDA (Food and Drug Administration), the US regulator. The IND asks permission to test the drug in humans. In the European Union, the equivalent is a Clinical Trial Application (CTA).

The FDA's own drug development overview is a clear, free primer.

Stage 2: Clinical trials (roughly 6 to 8 years)

Human testing runs in three main phases. Each phase is bigger, slower, and more expensive than the last.

Phase I: is it safe?

• Size: typically tens of patients (often 20 to 100).
• Goal: safety, dosing, and how the body processes the drug.
• Oncology note: unlike most diseases, cancer Phase I trials usually enroll patients with the disease, not healthy volunteers, because the drugs are too toxic to give to healthy people.

Here the team finds the tolerable dose and watches for dangerous side effects.

Phase II: does it work?

• Size: typically around 100 to 300 patients.
• Goal: early evidence of efficacy in the target cancer, plus more safety data.

Phase II is where hope meets reality. Many antibodies that were safe in Phase I simply do not shrink tumors enough. This is the single deadliest phase for attrition.

Phase III: is it better?

• Size: often hundreds to a few thousand patients, across many hospitals and countries.
• Goal: prove the drug works better than the current standard of care, in a large, controlled trial.
• Design: usually randomized and controlled, meaning patients are assigned by chance to the new drug or to a comparison group, to remove bias.

Phase III is the most expensive part of the entire pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète →. A single large oncology trial can cost hundreds of millions of dollars and run for years, because you must wait to see whether patients live longer.

Stage 3: Regulatory review and launch (roughly 1 to 2 years)

If the trials succeed, the company files a Biologics License Application (BLA) with the FDA (a New Drug Application, or NDA, for small molecules). The regulator reviews the full data package: safety, efficacy, and manufacturing.

Manufacturing matters more than newcomers expect. Regulators must confirm the company can make the biologic consistently and at scale. This is a whole discipline: CMC (Chemistry, Manufacturing, and Controls).

Approval is not the finish line. Phase IV (post-marketing surveillance) continues after launch to catch rare side effects that only appear across large populations.

The attrition math: why 90% fail

Combine the phase-by-phase survival rates and the picture is stark. Industry analyses, including work from MIT researchers, estimate that only about 1 in 10 drugs that enter Phase I ever reaches approval. Oncology tends to be worse than average, with success rates often cited in the single digits to low teens.

A rough way to see it:

• Enter Phase I: 100 candidates
• Survive to Phase II: perhaps 60
• Survive to Phase III: perhaps 30
• ReachReachThe number of unique people exposed to your message in a given period. Unlike impressions, reach counts each person once, no matter how often they see it.Voir la définition complète → approval: around 10

(These are illustrative estimates, not exact figures. Rates vary by disease area and data source.)

Each survivor has to pay for all the failures. That is the core economics of the industry.

The capital burn: what it actually costs

The most cited estimate for the cost of bringing one new drug to market, from a Tufts Center analysis, is around 2.6 billion dollars. That figure is debated and includes the cost of capital (the value of money tied up for a decade) and the cost of all the failures. Other estimates run lower. Treat any single number as an estimate, not gospel.

Where does the money go?

• Phase III trials are the largest single cost.
• Manufacturing biologics is expensive (living cells, sterile facilities).
• The time value of money is huge: a decade of spending before any revenue.

This is why biotech is structured around milestone financing. Startups raise money in rounds, each unlocked by hitting a data milestone (positive Phase II results, for example). A failed readout can end a company overnight.

It also explains the prevalence of licensing and partnership deals. A small biotech that generates strong Phase I or II data will often license the drug to a large pharmaceutical company that can fund Phase III and global launch. The deal usually includes an upfront payment, milestone payments tied to future success, and royalties on eventual sales.

Why the timeline and attrition shape everything

Understanding the pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète → explains behaviors that otherwise look strange.

Why drug prices are high. A launched drug has to recover the cost of itself plus the nine that failed, within the years remaining on its patent (the temporary exclusivity that lets the company sell without direct competition). When patents expire, cheaper biosimilars (near-copies of a biologic) enter and prices fall.

Why companies chase "de-risking" data. Every phase transition is a moment where value jumps or collapses. Investors pay close attention to trial readouts because they reprice the entire company.

Why regulators offer acceleration. For serious diseases with unmet need, the FDA has pathways such as Breakthrough Therapy and Accelerated Approval that can shorten timelines. These help, but they do not remove the fundamental risk.

Why partnering is the norm, not the exception. Few small companies can self-fund a Phase III oncology program. The capital and attrition math push toward collaboration.

A quick mental model

When you evaluate any biotech, ask three questions:

1. Where is the asset in the pipeline? (Preclinical is a lottery ticket. Phase III is a different risk profile entirely.)

2. What is the next data readout, and when? (That event will move value more than anything else.)

3. How is it funded to reach that readout? (Cash runway relative to the next milestone.)

These three questions capture most of what drives value in the sector.

Key takeaways

• The pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète → runs roughly 10 to 15 years and, by common estimates, over a billion dollars per approved drug, with Phase III trials as the largest cost.
• Attrition is the defining feature: only about 1 in 10 candidates that enter human trials reaches the market, and oncology is often harder than average.
• Phase II (does it work?) is typically the deadliest phase; Phase III (is it better than standard care?) is the most expensive.
• The economics of failure and long timelines explain high prices, patent-driven exclusivity, and the industry's heavy reliance on milestone financing and licensing deals.
• To assess any biotech asset, track its pipelinepipelineAll active sales opportunities across the stages of the sales process, together with their combined potential value and probability of closing.Voir la définition complète → stage, its next data readout, and whether it is funded to that milestone.