... is gene therapy, according to London-based boutique investment bank Mulier Capital, which is raising a $500 million Ingeneous Fund to invest in late-stage, listed gene-therapy companies.
Are they mad?, you ask. Gene therapy? That area steeped in controversy, which elicits visceral public reaction like no other? That dirty word that promised the world, yet delivered nothing more than disappointments, SCID kids, and the tragic, overexposed story of Jesse Gelsinger?
Yes, that’s the one. Now granted, these days, gene-based medicine encompasses all kinds of DNA-based drugs, not just traditional integrative gene therapy; the Mulier group also include the ultra-hot yet earlier-stage gene silencing approach, RNA interference, in their definition. Still, they reckon, it’s all about to happen. “Gene-based medicine is now 8.5 months’ pregnant,” declares Mulier’s founder and CEO Pieter Mulier, previously head of sales at Nomura.
So in order to be in the right place at the birth of this next big thing, the Fund will pool a series of “significant” stakes (up to 28%) in what Mulier describes as the best third of gene-technology companies, thereby spreading risk across about ten Phase III programs and over 30 Phase I or II programs, in earlier clinical phases. Investors will have access to the expertise of the Fund’s advisory board, which includes George Poste (needs no introduction), James Rothman, Chief Scientific Advisor at GE Healthcare, and Max Talbott, a Big Pharma veteran who is now SVP worldwide commercial development and gene-therapy firm Introgen. Given the size of the stakes it plans to buy, Ingeneous will in theory have the negotiating power to achieve the right valuation when (and if) Big Pharma does come bursting in.
Now, there’s no doubt that significant progress has been made in gene-based medicine. Having solved many of the technological problems hampering the field (most notably around delivery vectors) and learnt from its mistakes, the field now boasts about 30 Phase III programs (including Introgen’s delayed p53 tumor suppressor therapy Advexin), over 200 in Phase II, and a somewhat more comfortable FDA. This year has seen gene therapy IPOs—like Holland’s Amsterdam Molecular Therapeutics, which went out at the top of its range in June—and Big Pharma deals, like Oxford BioMedica’s March tie-up with Sanofi-Aventis for Phase III renal cancer immunotherapy TroVax.
But the inherent complexity of gene-based medicine—delivery system, drug, target, breadth of effect, duration of action—and still unanswered commercial questions (can these kinds of therapy make money? Are they practical to administer?) mean not everyone’s calling this the next monoclonal antibody revolution. As we’ll discuss in a forthcoming feature in START-UP, plenty of Big Pharma are still steering well clear; others like Johnson & Johnson are dipping cautious toes in via corporate VC. They, and similarly tentative VCs, are anxious not to miss out completely just incase gene therapy does take off.
It’s this tantalizing ‘what if’ that Mulier is trying to exploit in pulling in its investors, a mix of institutions and high net worths that Mulier says have already made $300 million worth of ‘soft’ commitments. If the first gene-based medicine is approved in 2008, as optimists expect, then perhaps the sector’s value will explode. But if anything goes wrong—even just one SAE, for instance, as in the case of Targeted Genetics’ AAV-delivered inflammatory arthritis candidate, which the Recombinant DNA Advisory Committee is still pondering over)—then there’s a serious risk that investors will be left high and dry.
So gene therapy’s still a gamble. But IN VIVO Blog agrees with Mulier in believing the odds look better than ever before.
Tuesday, September 18, 2007
The Next Big Thing...
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2 comments:
Steady tiger!
http://pharmagiles.blogspot.com/2007/09/peer-pressure.html
What is the Clinical Relevance of Gene Profiling?
The Microarray (gene chips) is a device that measures differences in gene sequence, gene expression or protein expression in biological samples. Microarrays may be used to compare gene or protein expression under different conditions, such as cells found in cancer.
Hence the headlong rush to develop tests to identify molecular predisposing mechansims whose presence still does not guarantee that a drug will be effective for an individual patient. Nor can they, for any patient or even large group of patients, discriminate the potential for clinical activity among different agents of the same class.
Genetic profiles are able to help doctors determine which patients will probably develop cancer, and those who will most likely relapse. However, it cannot be suitable for specific treatments for individual patients.
In the new paradigm of requiring a companion diagnostic as a condition for approval of new targeted therapies, the pressure is so great that the companion diagnostics they’ve approved often have been mostly or totally ineffective at identifying clinical responders (durable and otherwise) to the various therapies.
Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targeted treatment, the cancer cell may be able to use other routes. Targeting one pathway may not be as effective as targeting multiple pathways in a cancer cell.
Another challenge is to identify for which patients the targeted treatment will be effective. Tumors can become resistant to a targeted treatment, or the drug no longer works, even if it has previously been effective in shrinking a tumor. Drugs are combined with existing ones to target the tumor more effectively. Most cancers cannot be effectively treated with targeted drugs alone. Understanding “targeted” treatments begins with understanding the cancer cell.
If you find one or more implicated genes in a patient's tumor cells, how do you know if they are functional (is the encoded protein actually produced)? If the protein is produced, is it functional? If the protein is functional, how is it interacting with other functional proteins in the cell?
All cells exist in a state of dynamic tension in which several internal and external forces work with and against each other. Just detecting an amplified or deleted gene won't tell you anything about protein interactions. Are you sure that you've identified every single gene that might influence sensitivity or resistance to a certain class of drug?
Assuming you resolve all of the preceeding issues, you'll never be able to distinguish between susceptibility of the cell to different drugs in the same class. Nor can you tell anything about susceptibility to drug combinations. And what about external facts such as drug uptake into the cell?
Gene profiling tests, important in order to identify new therapeutic targets and thereby to develop useful drugs, are still years away from working successfully in predicting treatment response for individual patients. Perhaps this is because they are performed on dead, preserved cells that were never actually exposed to the drugs whose activity they are trying to assess.
It will never be as effective as the cell culture method, which exists today and is not hampered by the problems associated with gene expression tests. That is because they measure the net effect of all processes within the cancer, acting with and against each other in real time, and it tests living cells actually exposed to drugs and drug combinations of interest.
It would be more advantageous to sort out what's the best "profile" in terms of which patients benefit from this drug or that drug. Can they be combined? What's the proper way to work with all the new drugs? If a drug works extremely well for a certain percentage of cancer patients, identify which ones and "personalize" their treatment. If one drug or another is working for some patients then obviously there are others who would also benefit. But, what's good for the group (population studies) may not be good for the individual.
Patients would certainly have a better chance of success had their cancer been chemo-sensitive rather than chemo-resistant, where it is more apparent that chemotherapy improves the survival of patients, and where identifying the most effective chemotherapy would be more likely to improve survival above that achieved with "best guess" empiric chemotherapy through clinical trials.
It may be very important to zero in on different genes and proteins. However, when actually taking the "targeted" drugs, do the drugs even enter the cancer cell? Once entered, does it immediately get metabolized or pumped out, or does it accumulate? In other words, will it work for every patient?
All the validations of this gene or that protein provides us with a variety of sophisticated techniques to provide new insights into the tumorigenic process, but if the "targeted" drug either won't "get in" in the first place or if it gets pumped out/extruded or if it gets immediately metabolized inside the cell, it just isn't going to work.
To overcome the problems of heterogeneity in cancer and prevent rapid cellular adaptation, oncologists are able to tailor chemotherapy in individual patients. This can be done by testing "live" tumor cells to see if they are susceptible to particular drugs, before giving them to the patient. DNA microarray work will prove to be highly complementary to the parellel breakthrough efforts in targeted therapy through cell function analysis.
As we enter the era of "personalized" medicine, it is time to take a fresh look at how we evaluate new medicines and treatments for cancer. More emphasis should be put on matching treatment to the patient, through the use of individualized pre-testing.
Upgrading clinical therapy by using drug sensitivity assays measuring "cell death" of three dimensional microclusters of "live" fresh tumor cell, can improve the situation by allowing more drugs to be considered. The more drug types there are in the selective arsenal, the more likely the system is to prove beneficial.
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