Biotech Strategy Blog

Commentary on Science, Innovation & New Products with a focus on Oncology, Hematology & Cancer Immunotherapy

Posts from the ‘Biomarkers’ category

The duality and the dark side of biomarkers

Fall in Boston

Far too many cancer drugs end up being pursued for the wrong reasons in the wrong setting, which is a dreadful waste of time, money, and resources. The focus lately on speed has not helped matters either and yet companies often forget the first-in-class to market agent doesn’t guarantee best-in-class performance.

With the upcoming ENA and SITC meetings there will likely be a veritable smorgasbord of different immunotherapies being presented, not to mention a variety of new combinations or regimens to consider – how should we proceed in terms of thinking about the data coming out and which framework should we use to assess them?

In this post we offer some tips and perspective on how we should perhaps be thinking about outcome measures, and in particular the use of biomarkers, when it comes to interpreting the results from early phase clinical trials that will be presented at these meetings.

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Potential new targets and biomarkers for immunotherapy

While it is universally true much more attention is focused on success in clinical trials in the sense of patients who respond well to a particular therapy, this doesn’t mean we can’t learn from people who tumours either don’t respond to treatment up front or relapse early.

In our latest review, we look at three different examples of what we can learn from biomarkers of T cell exhaustion with both CAR-T cell therapies (with two different targets) as well as immune checkpoint blockade.

In short, there’s more to think about beyond antigen loss and target downregulation.

Why does this matter?

Well if we can identify markers of early relapse then we can either intervene earlier and switch to another therapy or we can add something else in to try and rescue the patient’s immune response.

Here we discuss some of the scientific findings from different research labs and explore how the information uncovered may be key to either future novel developments or clinical strategies with current immunotherapy approaches…

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New ways of thinking about the immune landscape

Earlier this year we highlighted how machine learning, artificial intelligence and big data might have an earlier than expected impact on clinical decision making. Quite a few sceptics scoffed at this idea.

Since then we have seen some nifty examples emerge at various conferences relating to clinical analyses such as this one at ASCO, although there have been quite a few others.

AACR Tumour Heterogeneity 2020

This latest post isn’t about deep learning per se though, but rather how can we look at the tumour microenvironment differently in ways which might help us make better or earlier clinical decisions?

There are a quite a few high profile examples where the emerging research is starting to look helpful so it’s time to link all the loose ends and take a thoughtful look at what we can learn from a particular example involving a high profile study.

The results, some of which intuitively make sense and others are surprising, may give us some useful clues of where to start looking next in terms future therapeutic interventions…

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ESMO20 Preview 1 – Key progress in biomarker development

Scaling the ramparts in Real Madrido

It feels slightly surreal to be writing about this year’s annual ESMO confab instead of attending in person in Madrid, Spain.

While much of the time and attention at ESMO is usually focused on the major phase 3 readouts from various clinical trials, we will be covering these during the meeting as they are presented to avoid repetition since many of the topline company trial results have already been announced.

In this year’s conference Preview series, I wanted to take a step back and explore early new product development in several forms:

  • Biomarkers and potential new ways of predicting outcomes in development
  • Emerging novel targets of interest
  • Developmental therapeutics – trials and tribulations

This initial review will tackle some important developments pertaining to various biomarkers of interest.

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The brightest flame casts the darkest shadow

George Martin’s quote seems rather apt this morning as NextCure announced there was disappointing single agent activity with their Siglec–15 directed agent (NC318) in an ongoing phase 1/2 trial.

There were a couple of initial partial responses reported at SITC last year and now it may seem as if the wheels are falling off the wagon.

What can we learn from the latest update?

It turns out quite a bit…

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The potential of innovative mouse models to recapitulate the microbiome of cancer patients

SITC 2019 Preview: After looking at exciting new developments in targeted therapies last week, it’s now time to switch horses and kick off our annual coverage of the Society for Immunotherapy of Cancer (SITC) meeting, which takes place in a few days time at National Harbor in Maryland.

National Harbor, MD

In the SITC 2019 Presidential Session this coming Saturday, one of the presentations we are eagerly looking forward to is by Dr Vyara Matson, a Post Doc in the lab of Dr Tom Gajewski at the University of Chicago.

Dr Matson will be presenting on “Patient-derived microbiota germ-free mouse model for identifying mechanisms of checkpoint blockade efficacy modulation.”

In our latest expert interview, we spoke to Dr Gajewski about the strategic concepts underpinning his work in the microbiome niche, where he has got to presently and where he plans to go next. It makes for fascinating reading, especially when you realise that as scientists, they are sceptical themselves and yet curious to discover the answers through carefully thought out experiments that could impact future patient care for those people receiving immunotherapy for the treatment of their particular cancer.

One major take home for us in following the cancer immunotherapy niche is that there could well be different mechanisms at play for primary and secondary resistance – where does the microbiome fit in with this, and can it be manipulated to create a more positive benefit?  Is the effect a real one or a spurious correlation?  These kind of questions, along with a host of others, are some of the key topics discussed in the expert interview.

If you have plans to be at #SITC2019 do let us know, as we always look forward to saying “hello” to BSB readers.

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Waves and waves of T cells

NKTR-214 Cover on Cancer Discovery

In the third part of our mini-series on cytokines, we get down and dirty with another pegylated IL-2 approach, this time from Nektar Therapeutics, including an interview with the PI, Dr Adi Diab from MD Anderson Cancer Centre and CSO, Dr Jonathan Zalevsky.

We’ve certainly had many full ranging discussions and chats with the good gentlemen; here we continue our journey to understand more about the science and underlying biology, as well as key biomarkers of response.

We can also be provocative too and put them on the spot regarding their critics and some of the pointed questions that get bandied about, which certainly makes for interesting reading.  Are they justified?

What should we be looking for when analysing the data?  You can find out for yourselves in the latest expert interview.

Other pertinent topics are also covered including where they’re headed and future data readouts to expect.

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How understanding patient tumours can help us with future IO trials

In wave 3 of the immuno-oncology surge things have slowed down, partly due to a raft of combination trials yet to read out and partly because the reality has finally hit that tumour heterogeneity means there will be variable patient responses.

Just getting from room to room on time can be a real challenge with 40,000 other people present!

This complexity can come about in many forms… immunosuppression, alterations in gene functions, resistance and immune escape, to name a few.

If we want to help more people respond to these therapies then before we can rush headlong into another round of combination trials, we first have to go back to looking carefully at the underlying biology of the diseases and listen to what the patient’s tumours are telling us in order to fix things.

To accomplish this feat requires considerable time, energy, effort, and a lot of bioinformatics.

In this post we explore five key talks that highlight different aspects of biomarkers of response and mechanisms of resistance.  From there, we may see additional validation and prospective testing to determine how best to segment people so that they have the greatest chance of responding to the therapy administered.

One thing that most people don’t have these days is time, which is how we can help you because here’s a handy short cut to finding out more about five complex and diverse areas on biomarkers or IO resistance quickly and easily…

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The Future of Cancer Immunotherapy Biomarkers

Continuing our in-depth oncology pathology interview with Dr David Rimm (Yale), we take a look at some of the new data his lab presented in Atlanta, where we are now with TMB as a biomarker, and what the future may hold for cancer immunotherapy biomarkers.

Early morning in Atlanta en route to the GWCC and AACR19

In an engaging discussion, Dr Rimm discussed many of the details behind PD-L1 and TMB in terms of what really matters when thinking about these tests and their practical applications. He also shared his candid thoughts on the lung cancer blood TMB data presented at AACR by Prof Solange Peters.

If you missed the first part of the interview with Dr David Rimm, a leading oncology pathologist at Yale, on the various challenges associated with PD-L1 as a biomarker on tumour and immune cells in triple negative breast cancer than you can catch up and read it here.

The second half of the interview with Dr Rimm focuses on TMB, with some more details on the challenges of reading PD-L1 on immune cells and why that is the case…

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The Yin and Yang of biomarkers in cancer research

Paths to success in cancer research

It’s time to pull together some notes, ideas, and clinical data on various biomarkers based on data available from clinical studies in oncology R&D and see how much progress we are making.

Are biomarkers a good path to success in cancer research or are they a gloomy red herring to the road less travelled?

Both answers can be equally true, but how do we tell the difference?  Are there any clues that we can use ahead of time to avoid later disappointment?

There have been several early studies that we’ve been following lately with readouts available from numerous cancer conferences, both positive and negative.

Can we learn from the failures and successes of the past to better interpret outcomes from future trials?

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