The issues we need to overcome before a patient walks into their doctor’s office

As co-founder and CEO of Organic pepperJon leads one of the world’s first transomics drug discovery companies.

I had my first migraine in college. More than a decade later, I was prescribed a cocktail of drugs – my saving grace. I could finally take control of my life and no longer cling to the ever-present worry that my migraines might steal days of my time and derail what I was working towards.

I had an ideal experience: diagnosis was possible, treatment was possible, and my response was positive. Unfortunately, many people with “incurable” diseases face the same debilitating physical threat from their disease, but lack the possibility of an objective diagnosis and lack treatment options.

An example is my grandmother, who was diagnosed with Alzheimer’s about 10 years ago and progressed dramatically about five years ago. Without access to disease-modifying treatments, my family watched her slip away.

To ensure that disease-modifying treatments will one day exist for today’s incurable diseases, we must optimize the processes that occur before patients arrive at the doctor’s office by addressing three key issues: l approach to identifying a drug target, understanding the impact of a drug and the approval process. .

Where is the target and what is it doing?

In November, Genentech, a subsidiary of Roche acquired for more than $40 billion in 2009, announced that its trial for an Alzheimer’s drug called gantenerumab had failed. Despite numerically superior performance to placebo in the Phase III GRADUATE I and GRADUATE II studies, gantenerumab did not meet its endpoints and statistical significance was not reached.

That came after Genentech and AC Immune failed in June of crenezumab, another Alzheimer’s drug. The phase II trial of crenezumab ended with inconclusive results on what the molecule did, whether it could modify Alzheimer’s disease, and whether further investigation into its impact was worth the cost of additional resources.

If this level of uncertainty around the effectiveness of molecules can come from one of the most resource-funded biotech companies in the world, what chance does small biotech have of determining the effectiveness of molecules at early stages? even earlier?

Even with genomic profiling, we lack the information needed early in the development process to understand which therapies hold promise. To reach this point, researchers must have access to comprehensive biological data that illuminates the true function of molecules against disease. With this information, we will be able to understand which drugs are most effective and least toxic before they reach the clinic and which drugs work best for certain patient populations.

What is the impact of the drug?

In mid-August, researchers from the University of Edinburgh and the University of Oxford published new findings on an Abbott drug, terazosin, prescribed for high blood pressure or an enlarged prostate. The results posit that terazosin may slow the progression of motor neuron diseases, such as ALS, by offsetting the progression of paralysis and improving survival.

To reuse terazosin, we would need to understand all of its effects and then tie them to a possible target for ALS. This particular application of the drug appears to be based purely on luck. However, if we had a systematic process to better understand the disease and the drugs, we could have identified them earlier in a much more structured way.

A step in the right direction would be to categorize diseases according to their causes rather than their symptoms. By doing so, all diseases of the same category can be treated in the same way. We are less likely to miss the promising solutions that come our way when we specifically target the factors that create or maintain disease, compared to pre-existing perceptions of disease for segmentation.

Now we need approval

Current time to market means that most patients diagnosed today with terminal and incurable diseases have no hope. Although the timeline varies, it typically takes 10 to 15 years to complete early non-clinical testing and three phases of clinical trials for FDA approval of a new drug.

Yet there are examples of private and public organizations working together to produce viable treatments through fast-track, non-traditional processes, such as Moderna’s Covid-19 vaccine, which received an EUA from the FDA about nine months ago. after Covid-19 hit the United States.

For people with terminal illnesses like cancer, which also kills millions every year, the urgency of treatment is no less urgent than Covid. People with incurable diseases deserve the same opportunities to receive life-changing therapies.

To advance therapies, improvements are needed across the drug development ecosystem. Stakeholders need to work together to standardize the collection of strong data, use impactful programs to decipher that data, and communicate results effectively to help regulators make informed decisions. With more consistent and reliable data to compare, the progress of promising solutions can move faster through regulatory processes to patients in need.


When I walked into my doctor’s office at age 25, my life changed for the better. Unseen years and billions of dollars have been invested in developing the drugs that freed me from the migraines that stole 20 of my days every month; I was lucky that this investment happened before I got to Dr. Diamond’s office.

We need to embrace tools that not only go beyond biological data standards to incorporate a broader layer of omic layers, but also tools that synthesize actionable insights from that data. We need this data to interact across disease domains, encouraging original thinking about how therapies for one “type” of disease can treat another.

We need access to this data at all stages, from preclinical to regulatory approval, to get promising treatments to the patients who need them faster, before it’s too late. To achieve this, biopharmaceutical drug developers must prioritize building data infrastructure to unlock the value of data sharing and collaboration and create massive innovation and value. Companies can also rely on biotech startups to help them manage and contextualize biodata.

All patients deserve to have a journey similar to mine. Once we recognize the shortcomings of our current processes, we can achieve this.

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