Major Challenges Biotech Startups Face in the Drug Development Process

The recognition of the common challenges US biotech startups face ahead of time accounts for more realistic valuations by investors, and a stronger chance of a successful project.
  • 2 months ago
  • 6 min read

Medical biotechnology is one of the hottest sectors in the biotech startups scene.

High-profile biotech startups in San Diego include anti-aging pioneer Samumed, now valued at over $12bn. Samumed has wowed venture capitalists with a never-ending pipeline of drugs, some of which are already on the market, and some in the late stage of development.

But while the likes of Samumed hog the business headlines, the reality for most drug projects is that they fail long before they even make it to the FDA approval stage.

A recent study showed that just 1 in every 5000 new drugs completes the journey from the lab to the bathroom cabinet.

Even formerly celebrated biotech companies in San Diego, such as Human Longevity Inc., have seen their valuations tumble 80% thanks to several failures in their attempts to extend life spans via tailored genetic research.

Why do most new drugs fail? Here are some of the most common reasons.

Drug development-related reasons

Drug development-related reasons for biotech failures

Drug development-related reasons for biotech failures

The clinical trial process is a long one

The average duration of a clinical trial in the US is a surprisingly lengthy 12 years. The highly regulated biotechnology space involves much unseen legal work needed to ensure that newly filed patents avoid conflicts with existing patents.

In the meantime, plenty of things can go wrong during clinical trials. And even if nothing goes wrong, the landscape itself can change, including changing market demand, changing science and changing regulatory requirements.

All this means that new drugs that looked completely viable at the start of the process can be rendered redundant a few years in.

Each stage in the process gets progressively more difficult

The drug development process is best visualized as a funnel, with each successive stage becoming increasingly difficult.

The first phase of a clinical trial involves an initial safety test, using a group of 100 or fewer volunteers. The aim of this stage is purely to assess safe dosages of the drug. This information is then used in phases II and III, testing the safety and efficacy of the drug in a small and large group of patients.

The likelihood of the drug not producing confirmatory data increases with each of the stages, resulting in a high rate of program failure.

Finding and keeping patients is complicated

Finding a sufficient number of naïve patients can be an issue, and the FDA will often require these patients to be restricted to a certain geographic area. What’s more, patient retention is often a challenge, particularly concerning drugs which are not life-threatening.

Patient data is resource-intensive to manage

Many biotechnology startups still rely on antiquated, time-consuming and expensive manual processes to maintain patient data.

This is particularly true in the task of finding and keeping in touch with candidate patients for clinical trials. Instead of hiring a large team of staff to sort through records and manually phone each patient, machine learning can make this process much more efficient. Automation of the patient engagement process cuts time and costs, while specialized software can analyze the thousands of pages of clinical trial protocol reports much faster than a human ever can.

EffectiveSoft’s biotechnology software development department designs custom tools to save start-ups valuable time and money. This can reduce the time spent in the clinical trial process by months or – in some cases, years – and can produce cost savings measured in the hundreds of millions of dollars annually.

Even FDA Approval is not the end of the story

Once a new drug is released to the public, the FDA requires that safety monitoring and ongoing research is required throughout the life cycle of the product. These so-called Phase IV Studies involve patient data collection which add further costs which must be factored into the development process.

Cost and funding сhallenges for biotechnology startups

Funding сhallenges for biotechnology startups

Funding сhallenges for biotechnology startups

Badly planned funding strategies

Startups in biotechnology are often guilty of underestimating how much funding their projects will require.

What’s more, choosing many smaller investors each with too little ‘skin in the game’, is a poor strategy for startup biotech companies, since that makes it easier for those investors to write off their investments at the first major hurdle.

Pharmaceutical companies and venture capitalists who provide much of the funding for biotechnology companies often expect much faster launches than is reasonable and often pull the plug before the project has a chance to show meaningful results.

Too much reliance on manual processes raises costs

Most new biotech startups which end in failure simply run out of money before reaching significant milestones. If these biomedical startups had just made some simple savings, they would have had a greater chance of lasting the distance.

And yet, many biotechnology companies rely on antiquated, time-consuming and expensive manual processes. Since each extra day of R&D can cost upwards of a million dollars, the company’s precious cash reserves quickly (and completely unnecessarily) get depleted.

US biotech is concentrated in a few hubs, raising costs yet further

One issue that the majority of biotech companies face in the United States is the fact that the industry is concentrated in a limited number of geographic locations.

This focus on the biotech startups in Bay Area, San Diego, and Boston may be useful in terms of collaboration and poaching research staff.

However, it also leads to high competition and high prices for lab space, employees and patients for the clinical trials, driving up costs yet further for fledgling biotechnology companies.

In contrast, companies in Europe do not face quite the same cost pressures, since their biotechnology sector is much more geographically distributed.

Conclusion

Medical biotechnology clearly offers innovators and investors the potential for market-beating returns. However, the flip side of this is an extremely high-risk of failure.

Each new drug program has the odds of a successful outcome severely stacked against it.

While the risk of a clinical trial failing to produce the desired outcome is inherently difficult to mitigate, many of the project costs faced by biotech startups are very easy to control and optimize.

For example, making use of the latest medical biotechnology software development tools can significantly reduce costs, by streamlining processes and automating certain tasks.

What’s more, recognizing the common problems which US biotech startups encounter at an earlier time, allows for more realistic valuations by investors, and a greater chance of a successful project.

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