Ever since the Human #Genome Project got rolling about thirty years ago (!) there’s been a lot of hope, and a lot of hype, about “#personalized #medicine” or “#precision medicine.” When it became clear that as always, the results weren’t going to match the hype, a lot of the hope went away too. This is a mistake.

I’d like to talk about a quiet revolution in precision medicine: #genetic #dosage guidelines, a.k.a. #pharmacogenomic #labeling. The basic idea is that if you carry certain genetic #variants, you may need considerably more or less of a particular medication than the standard dose. Back in the ’90s, the kind of genetic #analysis needed to make use of that information was far too expensive and time-consuming for #clinical practice. These days you can get a complete #sequence in a matter of hours, for the same cost as a battery of standard blood tests.

Fifteen years ago or so, the FDA approved the first pharmacogenomic labeling, for #warfarin. I was lucky enough to be in the room when the researchers made the announcement, and you could have heard a pin drop. Now it’s routine, and there’s a very long list: https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling

Everyone reacts to #medications differently. For most patients, most medications, and most diseases, there’s a fairly broad range of clinical effectiveness between “too little to do any good” and “way too much.” But for a substantial number of all of the above, the range is much narrower—and when you add up all the special cases, you get a hell of a lot of people!

A lot of #drugs never get approved, despite showing promise in clinical #trials, because they only help a portion of the study population. Regulatory bodies like the #FDA are notoriously resistant to #subgroup analysis, and I get why: it’s very easy to cherry-pick those subjects in a clinical trial who happen to do well, and then come up with a post hoc explanation for why the test treatment worked for them but not for other participants. Some bad drugs have made it to market because of this kind of chicanery. But of course sometimes there’s a real reason one group does better, and as long as genetic testing is part of the study design from the start, it’s becoming possible to convince regulators that reason is valid.

My work is mostly upstream of this, in the drug #target #discovery phase: finding disease-related #genes and #proteins that might be modifiable with the right medication. Since it’s part of the project from the start, that makes trial design easier, and the results more likely to be accepted. But I’d really like to see more #genomic analysis on drugs that aren’t designed that way too, and I think we’re getting there.

Genetic dosage guidelines, though, are making a real difference in current practice. There are still considerable debates over the merits of many labelings, driven partly by legitimate #statistical concerns and partly by ideology. But the principle is proven beyond reasonable doubt, and it’s saving lives and relieving suffering right now, every day. Much more to come.

Ever since the Human #Genome Project got rolling about thirty years ago (!) there’s been a lot of hope, and a lot of hype, about “#personalized #medicine” or “#precision medicine.” When it became clear that as always, the results weren’t going to match the hype, a lot of the hope went away too. This is a mistake.

I’d like to talk about a quiet revolution in precision medicine: #genetic #dosage guidelines, a.k.a. #pharmacogenomic #labeling. The basic idea is that if you carry certain genetic #variants, you may need considerably more or less of a particular medication than the standard dose. Back in the ’90s, the kind of genetic #analysis needed to make use of that information was far too expensive and time-consuming for #clinical practice. These days you can get a complete #sequence in a matter of hours, for the same cost as a battery of standard blood tests.

Fifteen years ago or so, the FDA approved the first pharmacogenomic labeling, for #warfarin. I was lucky enough to be in the room when the researchers made the announcement, and you could have heard a pin drop. Now it’s routine, and there’s a very long list: https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling

Everyone reacts to #medications differently. For most patients, most medications, and most diseases, there’s a fairly broad range of clinical effectiveness between “too little to do any good” and “way too much.” But for a substantial number of all of the above, the range is much narrower—and when you add up all the special cases, you get a hell of a lot of people!

A lot of #drugs never get approved, despite showing promise in clinical #trials, because they only help a portion of the study population. Regulatory bodies like the #FDA are notoriously resistant to #subgroup analysis, and I get why: it’s very easy to cherry-pick those subjects in a clinical trial who happen to do well, and then come up with a post hoc explanation for why the test treatment worked for them but not for other participants. Some bad drugs have made it to market because of this kind of chicanery. But of course sometimes there’s a real reason one group does better, and as long as genetic testing is part of the study design from the start, it’s becoming possible to convince regulators that reason is valid.

Much of my work is upstream of this, in the drug #target #discovery phase: finding disease-related #genes and #proteins that might be modifiable with the right medication. Since it’s part of the project from the start, that makes trial design easier, and the results more likely to be accepted. But I’d really like to see more #genomic analysis on drugs that aren’t designed that way too, and I think we’re getting there.

Genetic dosage guidelines, though, are making a real difference in current practice. There are still considerable debates over the merits of many labelings, driven partly by legitimate #statistical concerns and partly by ideology. But the principle is proven beyond reasonable doubt, and it’s saving lives and relieving suffering right now, every day. Much more to come.

Ever since the Human #Genome Project got rolling about thirty years ago (!) there’s been a lot of hope, and a lot of hype, about “personalized medicine” or “precision medicine.” When it became clear that as always, the results weren’t going to match the hype, a lot of the hope went away too. This is a mistake.

I’d like to talk about a quiet revolution in precision medicine: #genetic #dosage guidelines, a.k.a. #pharmacogenomic #labeling. The basic idea is that if you carry certain genetic #variants, you may need considerably more or less of a particular medication than the standard dose. Back in the ’90s, the kind of genetic #analysis needed to make use of that information was far too expensive and time-consuming for #clinical practice. These days you can get a complete #sequence in a matter of hours, for the same cost as a battery of standard blood tests.

Fifteen years ago or so, the FDA approved the first pharmacogenomic labeling, for #warfarin. I was lucky enough to be in the room when the researchers made the announcement, and you could have heard a pin drop. Now it’s routine, and there’s a very long list: https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling

Everyone reacts to #medications differently. For most patients, most medications, and most diseases, there’s a fairly broad range of clinical effectiveness between “too little to do any good” and “way too much.” But for a substantial number of all of the above, the range is much narrower—and when you add up all the special cases, you get a hell of a lot of people!

A lot of #drugs never get approved, despite showing promise in clinical #trials, because they only help a portion of the study population. Regulatory bodies like the #FDA are notoriously resistant to #subgroup analysis, and I get why: it’s very easy to cherry-pick those subjects in a clinical trial who happen to do well, and then come up with a post hoc explanation for why the test treatment worked for them but not for other participants. Some bad drugs have made it to market because of this kind of chicanery. But of course sometimes there’s a real reason one group does better, and as long as genetic testing is part of the study design from the start, it’s becoming possible to convince regulators that reason is valid.

Much of my work is upstream of this, in the drug #target #discovery phase: finding disease-related #genes and #proteins that might be modifiable with the right medication. Since it’s part of the project from the start, that makes trial design easier, and the results more likely to be accepted. But I’d really like to see more #genomic analysis on drugs that aren’t designed that way too, and I think we’re getting there.

Genetic dosage guidelines, though, are making a real difference in current practice. There are still considerable debates over the merits of many labelings, driven partly by legitimate #statistical concerns and partly by ideology. But the principle is proven beyond reasonable doubt, and it’s saving lives and relieving suffering right now, every day. Much more to come.