Adrian Hayday. Crick

Adri­an Hay­day re­futes chal­lenge on in­flu­en­tial au­toan­ti­body pa­per by Karolin­s­ka sci­en­tists

Back in 2016, Adri­an Hay­day and his col­leagues at King’s Col­lege Lon­don — to­geth­er with some col­lab­o­ra­tors in Ger­many and Es­to­nia — made a splash in the im­munol­o­gy world with a pa­per, pub­lished in Cell, sug­gest­ing that pa­tients with a par­tic­u­lar ge­net­ic de­fect pro­duce more au­toan­ti­bod­ies than pre­vi­ous­ly known. These self-gen­er­at­ed an­ti­bod­ies, they pro­posed, of­fered ther­a­peu­tic po­ten­tial for au­toim­mune dis­eases, most promi­nent­ly Type 1 di­a­betes.

The re­sults formed the foun­da­tion of a Ger­man biotech dubbed Im­muno­Qure, which lat­er inked a part­ner­ship with France’s Servi­er to pur­sue an au­toan­ti­body that found to neu­tral­ize in­ter­fer­on-α. Servi­er pledged up to €164 mil­lion to the deal.

Nils Lan­de­gren

It al­so piqued the in­ter­est of Nils Lan­de­gren, a pro­fes­sor at the Karolin­s­ka In­sti­tute who’s spent years de­cod­ing the au­toim­mune reg­u­la­tor gene (AIRE) and its de­fi­cien­cy. While he’s helped iden­ti­fy a num­ber of bona fide au­toanti­gens in au­toim­mune poly­en­docrine syn­drome type 1, the vast num­ber of au­toan­ti­bod­ies iden­ti­fied in the Cell pa­per caught him by sur­prise. And he want­ed to see if there was re­al­ly a link be­tween one of the known au­toanti­gens to Type 1 di­a­betes. So he took a cou­ple of ex­ist­ing datasets and then ran his own analy­sis with a team from Swe­den and the US.

Long sto­ry short: They couldn’t repli­cate the re­sults.

“We could show that us­ing ran­dom da­ta, we got ba­si­cal­ly the same re­sult they did,” Lan­de­gren told Med­Scape. “We have a very strong case their re­sults are false.”

In a re­sponse to the pa­per, Hay­day stood by his re­sults and the meth­ods brought in­to ques­tion, coun­ter­ing that “flaws in de­sign and im­ple­men­ta­tion in­val­i­date this chal­lenge.”

“While we wel­come open, con­struc­tive dis­course about sci­ence, we are dis­ap­point­ed by this dis­pute be­cause we be­lieve it re­flects sim­ple but im­por­tant dif­fer­ences be­tween our ap­proach­es that could have been eas­i­ly re­solved, had Lan­de­gren and co-work­ers ap­proached us di­rect­ly,” his team wrote.

The dis­putes are two-pronged. The first has to do with the num­ber of au­toan­ti­bod­ies APS1 pa­tients har­bor. Hay­day’s group — with Stef­fen Mey­er and Mar­tin Wood­ward — as co-first au­thors found that col­lec­tive­ly hit over more than 3,700 hu­man pro­teins out of the 9,000 screened. But when Lan­de­gren’s team ran their sam­ples against the same as­say, they found “on­ly a very re­strict­ed set of pro­teins (<1% of the pro­tein pan­el) are tar­get­ed by au­toan­ti­bod­ies in mul­ti­ple APS1 pa­tients.”

The sta­tis­ti­cal method de­ployed for the pa­tient group ver­sus the con­trol, Lan­de­gren wrote, skewed the re­sults to show high­er lev­els of au­toan­ti­body sig­nals than in re­al­i­ty.

To bet­ter de­ter­mine how the an­a­lyt­i­cal bias in­flu­enced the over­all re­sults, we ap­plied a re­versed cut­off to our dataset based on the val­ues ob­tained for the 51 APS1 pa­tients in­stead of those for the 21 healthy con­trols. The healthy con­trols now turned out to show greater num­bers of high-lev­el (Z ≥ 5) au­toan­ti­body sig­nals than the APS1 pa­tients, re­veal­ing that the skew­ing ef­fect of the da­ta analy­sis was dom­i­nat­ing the re­sults.

To be sure, the 2016 pa­per had a stat­ed in­ter­est in find­ing pa­tients’ “pri­vate au­toan­ti­body reper­toire” — which might not be shared with oth­ers.

“When you un­der­take a sta­tis­ti­cal treat­ment of da­ta, there is no sil­ver bul­let, you have to use what makes sense,” he said to Med­Scape.

Even if they ap­ply a more con­ser­v­a­tive sta­tis­ti­cal ap­proach, he wrote in his re­sponse, they “iden­ti­fied re­ac­tiv­i­ties over­lap­ping 81% with our orig­i­nal study: again, these com­prised broad­ly shared au­toanti­gens and from ~30 to~100 pri­vate speci­fici­ties that col­lec­tive­ly com­posed a sub­stan­tial frac­tion of the pro­teome.”

Per­haps more point­ed­ly, Lan­de­gren’s team at­tempt­ed to poke holes in the cor­re­la­tion be­tween hav­ing neu­tral­iz­ing au­toan­ti­bod­ies of in­ter­fer­on-α and be­ing free of Type 1 di­a­betes. Hay­day’s the­o­ry was that an­ti-IFNα an­ti­bod­ies ap­peared to pro­tect APS1 pa­tients from ul­ti­mate­ly de­vel­op­ing that dis­ease, sup­port­ing pre­vi­ous claims that type I IFN con­tributes to Type 1 di­a­betes,

Writ­ing in eLife — where they went af­ter get­ting turned down by Cell — Lan­de­gren re­port­ed strong neu­tral­iza­tion of type 1 IFN in all APS1 sam­ples, not just the ones from di­a­bet­ics (a find­ing that Hay­day dis­missed as a re­sult of a “shod­dy ex­per­i­ment” con­duct­ed with less sen­si­tive meth­ods.)

“[A]t high con­cen­tra­tions, the sera of pa­tients with and with­out T1D showed com­pa­ra­ble ac­tiv­i­ties, but at low­er, sub-sat­u­ra­tion con­cen­tra­tions [50-fold di­lu­tions], the co­hort with­out T1D showed sig­nif­i­cant­ly greater ca­pac­i­ty to lim­it IFNα ac­tiv­i­ty,” Hay­day et al wrote in their re­sponse.

They added that the oth­er cen­tral ob­ser­va­tions from their 2016 pa­per re­mained un­chal­lenged: that APS1 pa­tients share nat­u­ral­ly aris­ing au­toan­ti­bod­ies to a small sub­set of pro­teins that are of ex­treme­ly high affin­i­ty.

Im­muno­Qure is still in the CMC stage for its drug can­di­date tar­get­ing IFN-α, but they won’t ex­act­ly be the first. As­traZeneca re­cent­ly con­ced­ed a Phase III de­feat for an­i­frol­um­ab in lu­pus, an an­ti­body that hits the re­cep­tors for IFN-α, IFN-β and IFN-ω. The hope is that by hit­ting the cy­tokines di­rect­ly — a “very dif­fer­ent modal­i­ty” — their nov­el pan an­ti-Type I IFN neu­tral­iz­ing an­ti­body will work “far more ef­fec­tive­ly” than the ex­ist­ing mAbs pro­duced by As­traZeneca or Genen­tech, Hay­day added.

De­vel­op­ment of the Next Gen­er­a­tion NKG2D CAR T-cell Man­u­fac­tur­ing Process

Celyad’s view on developing and delivering a CAR T-cell therapy with multi-tumor specificity combined with cell manufacturing success
Overview
Transitioning potential therapeutic assets from academia into the commercial environment is an exercise that is largely underappreciated by stakeholders, except for drug developers themselves. The promise of preclinical or early clinical results drives enthusiasm, but the pragmatic delivery of a therapy outside of small, local testing is most often a major challenge for drug developers especially, including among other things, the manufacturing challenges that surround the production of just-in-time and personalized autologous cell therapy products.

Paul Hudson, Getty Images

UP­DAT­ED: Sanofi CEO Hud­son lays out new R&D fo­cus — chop­ping di­a­betes, car­dio and slash­ing $2B-plus costs in sur­gi­cal dis­sec­tion

Earlier on Monday, new Sanofi CEO Paul Hudson baited the hook on his upcoming strategy presentation Tuesday with a tell-tale deal to buy Synthorx for $2.5 billion. That fits squarely with hints that he’s pointing the company to a bigger future in oncology, which also squares with a major industry tilt.

In a big reveal later in the day, though, Hudson offered a slate of stunners on his plans to surgically dissect and reassemble the portfoloio, saying that the company is dropping cardio and diabetes research — which covers two of its biggest franchise arenas. Sanofi missed the boat on developing new diabetes drugs, and now it’s pulling out entirely. As part of the pullback, it’s dropping efpeglenatide, their once-weekly GLP-1 injection for diabetes.

“To be out of cardiovascular and diabetes is not easy for a company like ours with an incredibly proud history,” Hudson said on a call with reporters, according to the Wall Street Journal. “As tough a choice as that is, we’re making that choice.”

Endpoints News

Keep reading Endpoints with a free subscription

Unlock this story instantly and join 67,300+ biopharma pros reading Endpoints daily — and it's free.

Roger Perlmutter, Merck

#ASH19: Here’s why Mer­ck is pay­ing $2.7B to­day to grab Ar­Qule and its next-gen BTK drug, lin­ing up Eli Lil­ly ri­val­ry

Just a few months after making a splash at the European Hematology Association scientific confab with an early snapshot of positive data for their BTK inhibitor ARQ 531, ArQule has won a $2.7 billion buyout deal from Merck.

Merck is scooping up a next-gen BTK drug — which is making a splash at ASH today — from ArQule in an M&A pact set at $20 a share $ARQL. That’s more than twice Friday’s $9.66 close. And Merck R&D chief Roger Perlmutter heralded a deal that nets “multiple clinical-stage oral kinase inhibitors.”

This is the second biotech buyout pact today, marking a brisk tempo of M&A deals in the lead-up to the big JP Morgan gathering in mid-January. It’s no surprise the acquisitions are both for cancer drugs, where Sanofi will try to make its mark while Merck beefs up a stellar oncology franchise. And bolt-ons are all the rage at the major pharma players, which you could also see in Novartis’ recent $9.7 billion MedCo buyout.

ArQule — which comes out on top after their original lead drug foundered in Phase III — highlighted early data on ‘531 at EHA from a group of 6 chronic lymphocytic leukemia patients who got the 65 mg dose. Four of them experienced a partial response — a big advance for a company that failed with earlier attempts.

Endpoints News

Keep reading Endpoints with a free subscription

Unlock this story instantly and join 67,300+ biopharma pros reading Endpoints daily — and it's free.

Paul Hudson, Sanofi

Paul Hud­son promis­es a bright new fu­ture at Sanofi, kick­ing loose me-too drugs and fo­cus­ing on land­mark ad­vances. But can he de­liv­er?

Paul Hudson was on a mission Tuesday morning as he stood up to address Sanofi’s new R&D and business strategy.

Still fresh into the job, the new CEO set out to convince his audience — including the legions of nervous staffers inevitably devoting much of their day to listening in — that the pharma giant is shedding the layers of bureaucracy that had held them back from making progress in the past, dropping the duds in the pipeline and reprioritizing a more narrow set of experimental drugs that were promised as first-in-class or best-in-class.  The company, he added, is now positioned to “go after other opportunities” that could offer a transformational approach to treating its core diseases.

Endpoints News

Keep reading Endpoints with a free subscription

Unlock this story instantly and join 67,300+ biopharma pros reading Endpoints daily — and it's free.

Am­gen puts its foot down in shiny new South San Fran­cis­co hub as it re­or­ga­nizes R&D ops

Amgen has signed up to be AbbVie’s neighbor in South San Francisco as it moves into a nine-story R&D facility in the booming biotech hub.

The arrangement gives Amgen 240,000 square feet of space on the Gateway of Pacific Campus, just a few minutes drive from its current digs at Oyster Point. The new hub will open in 2022 and house the big biotech’s Bay Area employees working on cardiometabolic, inflammation and oncology research.

Ab­b­Vie, Scripps ex­pand part­ner­ship, for­ti­fy fo­cus on can­cer drugs

Scripps and AbbVie go way back. Research conducted in the lab of Scripps scientist Richard Lerner led to the discovery of Humira. The antibody, approved by the FDA in 2002 and sold by AbbVie, went on to become the world’s bestselling treatment. In 2018, the drugmaker and the non-profit organization signed a pact focused on developing cancer treatments — and now, the scope of that partnership has broadened to encompass a range of diseases, including immunological and neurological conditions.

Left top to right: Mark Timney, Alex Denner, Vas Narasimhan. (The Medicines Company, Getty, AP/Endpoints News)

In a play-by-play of the $9.7B Med­Co buy­out, No­var­tis ad­mits it over­paid while of­fer­ing a huge wind­fall to ex­ecs

A month into his tenure at The Medicines Company, new CEO Mark Timney reached out to then-Novartis pharma chief Paul Hudson: Any interest in a partnership?

No, Hudson told him. Not now, at least.

Ten months later, Hudson had left to run Sanofi and Novartis CEO Vas Narasimhan was paying $9.7 billion for the one-drug biotech – the largest in the string of acquisitions Narasimhan has signed since his 2017 appointment.

The deal was the product of an activist investor and his controversial partner working through nearly a year of cat-and-mouse negotiations to secure a deal with Big Pharma’s most expansionist executive. It represented a huge bet in a cardiovascular field that already saw two major busts in recent years and brought massive returns for two of the industry’s most eye-raising names.

Endpoints News

Keep reading Endpoints with a free subscription

Unlock this story instantly and join 67,300+ biopharma pros reading Endpoints daily — and it's free.

South Ko­rea jails 3 Sam­sung ex­ecs for de­stroy­ing ev­i­dence in Bi­o­Log­ics probe

Three Samsung executives in Korea are going to jail.

The convictions came in what prosecutors had billed as “biggest crime of evidence destruction in the history of South Korea”: a case of alleged corporate intrigue that was thrown open when investigators found what was hidden beneath the floor of a Samsung BioLogics plant. Eight employees in total were found guilty of evidence tampering and the three executives were each sentenced to up to two years in prison.

Nick Plugis, Avak Kahvejian, Cristina Rondinone, Milind Kamkolkar and Chad Nusbaum. (Cellarity)

Cel­lar­i­ty, Flag­ship's $50M bet on net­work bi­ol­o­gy, mar­ries ma­chine learn­ing and sin­gle-cell tech for drug dis­cov­ery

Cellarity started with a simple — but far from easy — idea that Avak Kahvejian and his team were floating around at Flagship Pioneering: to digitally encode a cell.

As he and his senior associate Nick Plugis dug deeper into the concept, they found that most of the models others have developed take a bottom-up approach, where they assemble the molecules inside cells and the connections between them from scratch. What if they opt for a top-down approach, aided by single-cell transcriptomics and machine learning, to gauge the behavior of the entire cellular network?