Pharmaceutical manufacturers are particularly vulnerable to securities fraud claims arising from the manufacturers’ pronouncements about safety or efficacy, the evidence for which is often statistical in nature. Safety claims may involve complex data sets, both from observational studies and clinical trials. Efficacy claims are typically based upon clinical trial data.
Publicly traded manufacturers may find themselves caught between competing securities regulations. In evaluating safety or efficacy data, manufacturers will often consult with an outside science advisory board, or report to regulatory agencies. Securities regulations specify that any disclosure of confidential inside information to an outsider triggers an obligation of prompt public disclosure of that information.[1] Companies also routinely seek to keep investors informed of research and marketing developments. Generally, manufacturers will make their public disclosures through widely circulated press releases.[2] Not surprisingly, disgruntled investors may challenge the accuracy of the press releases, when the product or drug turns out to be less efficacious or more harmful than represented in the press release. These challenges, brought under the securities laws, often are maintained in parallel to product liability actions, sometimes in the same multi-district litigation.
Securities laws require accurate disclosure of all material information.[3] Rule 10b-5 of the Securities Exchange Commission (SEC) prohibits any person from making “any untrue statement of material fact” or from omitting “a material fact necessary in order to make the statements made, in light of the circumstances under which they were made, not misleading.”[4]
A prima facie case of securities fraud requires that plaintiff allege and establish, among other things, a material misrepresentation or omission.[5] The obligations to speak and to speak accurately have opened manufacturers to second guessing in their analyses of safety and efficacy data. In most securities fraud cases, courts have given manufacturers a wide berth by rejecting differences in opinions about the proper interpretation of studies as demonstrating fraud under the securities regulations.[6] This latitude has been given both in judgment of what test procedures to use, as well as in how best to interpret data.[7] In Padnes v. Scios Nova Inc., the manufacturer was testing a drug for treatment of acute kidney failure. Scios Nova issued a press release after its phase II trial, to announce a statistically significant reduction in patients’ need for dialysis. When the early phase III results failed to confirm this result, plaintiffs sued Scios Nova for not disclosing the lack of statistically significant outcomes on other measures of kidney function, as well as for its interpretation of dialysis results as statistically significant.[8] The trial court dismissed the complaint.[9]
Several securities fraud cases have turned on investor dissatisfaction on how companies interpreted clinical trial subgroup data. In Noble Asset Management v. Allos Therapeutics, Inc.,[10] the company issued a press release, noting no statistically significant increase overall in survival advantage from a drug for breast cancer, but also noting a statistically significant increased survival in a non-prespecified subgroup of patients with metastatic breast cancer.[11] The plaintiff investors claimed that the company should have disclosed that the FDA was unlikely to approve an indication based upon an ad hoc subgroup analysis, but the trial court rejected this claim because FDA policy on drug approvals is public and well known.[12] The plaintiffs also complained that the press release referred to statistically significant results from a Cox multiple regression analysis rather than the log-rank (non-parametric survival) analysis required by FDA. The trial court rejected this claim as well, opining that the analysis was not misleading when the company correctly reported the raw data and the results of the Cox multiple regression analysis.[13]
Two recent appellate decisions emphasize the courts’ unwillingness to scrutinize the contested statistical methodology that underlies plaintiffs’ claims of misrepresentation. In In re Rigel Pharmaceuticals, Inc. Securities Litigation, the plaintiff investors were dissatisfied, not with reporting of subgroups, but rather with the failure of the company to report geographic subgroup results, as well as its use of allegedly improper statistical tests and its failure to account for multiple comparisons.[14]
The Ninth Circuit affirmed the dismissal of a complaint. The appellate court held that allegations of “statistically false p-values” were not sufficient; plaintiffs must allege facts that explain why the difference between two statements “is not merely the difference between two permissible judgments, but rather the results of a falsehood.”[15] Alleging that a company should have used a different statistical method to analyze the data from its clinical trial is not sufficient to raise an issue of factual falsity under the securities fraud statute and regulations.[16] The Court explained that the burden was on plaintiffs to plead and prove that the difference between two statistical statements “is not merely the difference between two permissible judgments, but rather the result of a falsehood.”[17] The Court characterized the plaintiffs’ allegations to be about judgments of which statistical tests or methods are appropriate, and not about false statements. Furthermore, the Court emphasized that the company’s statistical method was called for in the trial protocol, and was selected before the data were unblinded and provided to the company.[18]
In Kleinman v. Elan Corporation[19], the Second Circuit affirmed the dismissal of a securities fraud class action against two pharmaceutical joint venturers, which issued a challenged press release on interim phase II clinical trial results for bapineuzumab, a drug for mild- to moderate-Alzheimer’s disease. The press release at issue announced “top line” findings and promised a full review at an upcoming international conference.[20] According to the release, the clinical trial data did not show a statistically significant benefit on the primary efficacy end point, but “[p]ost-hoc analyses did show statistically significant and clinically meaningful benefits in important subgroups.”[21]
The plaintiffs in Kleinman complained that the clinical trial had started with crucial imbalances between drug and placebo arms, thus indicating a failure in randomization, and that the positive results had come from impermissible post-hoc subgroup analyses.[22] The appellate court appeared not to take the randomization issue seriously, and rejected the notion that statements can be false when they represent a defendant company’s reasonable interpretation of the data, even when the interpretation later turns out to be shown to be false[23]:
“At bottom, Kleinman simply has a problem with using post-hoc analyses as a methodology in pharmaceutical studies. Kleinman cites commentators who liken post-hoc analyses to moving the goal posts or shooting an arrow into the wall and then drawing a target around it. Nonetheless, when it is clear that a post-hoc analysis is being used, it is understood that those results are less significant and should have less impact on investors. Our job is not to evaluate the use of post-hoc analysis in the scientific community; the FDA has already done so.”
In United States v. Harkonen[24], the government turned the law of statistical analyses in securities fraud on its head, when it prosecuted a pharmaceutical company executive for his role in issuing a press release on clinical trial data. The jury acquitted Dr. Harkonen on a charge of misbranding[25], but convicted on a single count of wire fraud.[26] Dr. Harkonen’s crime? Bad statistical practice.
The government conceded that the data represented in the press release were accurate, as were the calculated p-values. The chargeable offense lay in Dr. Harkonen’s describing the clinical trial results as “demonstrating a survival benefit” of the biological product (interferon γ-1b) in a clinical trial subgroup of patients with mild- to moderate-idiopathic pulmonary fibrosis. The p-value for the subgroup was 0.004, with an effect size of 70% reduction in mortality. The subgroup, however, was not prespecified, and was not clearly labeled as a post-hoc analysis. The trial had not achieved statistical significant on its primary end point.
In prosecuting Dr. Harkonen, the government offered no expert witness opinion. Instead, it relied upon a member of the clinical trial’s data safety monitoring board, who advanced a strict, orthodox view that if the primary end point of a trial “failed,” then the data could not be relied upon to infer any meaningful causal connection within secondary end points, let alone non-prespecified end points. The prespecified survival secondary end point showed a 40 percent reduction in mortality, p = 0.08 (which shrank to 0.055 on an intent-to-treat analysis). The press release also relied upon a previous small clinical trial that showed a benefit in survival at five years, with the therapy group at 77.8%, compared with 16.7% in the control groups, p = 0.009.
The trial court accepted the government’s claim that p-values less than 0.05 were something of “magic numbers,”[27] and rejected post-trial motions for accquittal. Dr. Harkonen’s use of “demonstrate” to describe a therapeutic benefit was, in the trial court’s view, fraudulent, because of the lack of “statistical significance” on the primary end point, and the multiple testing with respect to the secondary survival end point. The Ninth Circuit affirmed the judgment of conviction in an unpublished per curiam opinion[28].
In contrast to the criminal wire fraud prosecution, the civil fraud actions against Dr. Harkonen and the company were dismissed.[29] The prosecution and the judgment in United States v. Harkonen is at odds with the latitude afforded companies in securities fraud cases. Furthermore, the case cannot be fairly squared with the position that the government took as an amicus curiae in Matrixx Initiatives, Inc. v. Siracusano[30], where the Solicitor General’s office, along with counsel for the Food and Drug Division of the Department of Health & Human Services, in their zeal to assist plaintiffs on claims against an over-the-counter pharmaceutical manufacturer, disclaimed the necessity, or even the importance, of statistical significance[31]:
“[w]hile statistical significance provides some indication about the validity of a correlation between a product and a harm, a determination that certain data are not statistically significant … does not refute an inference of causation.”
Suddenly, when prosecuting an unpopular pharmaceutical company executive, the government’s flexibility evaporated. Government duplicity was a much greater problem than statistical multiplicity in Harkonen.[32]
[1] Security Exchange Comm’n Regulation FD, 17 C.F.R. § 243.100 (requiring prompt public disclosure of any confidential, material inside information after disclosed to non-insiders).
[2] Selective Disclosure and Insider Trading, Securities Act Release No. 7881, Fed. Sec. L. Rep. (CCH) ¶ 86,319 (Aug. 15, 2000) (“As a general matter, acceptable methods of public disclosure for purposes of Regulation FD will include press releases distributed through a widely circulated news or wire service . . . .”).
[3] Section 10(b) of the Exchange Act of 1934 prohibits any person “[t]o use or employ, in connection with the purchase or sale of any security . . . any manipulative or deceptive device or contrivance in contravention of such rules and regulations as the [Securities and Exchange Commission] may prescribe.” 15 U.S.C. § 78j(b).
[4] 17 C.F.R. § 240.10b-5.
[5] Stoneridge Inv. Partners LLC v. Scientific-Atlanta, 552 U.S. 148, 157 (2008) (“(1) a material misrepresentation or omission []; (2) scienter; (3) a connection between the misrepresentation or omission and the purchase or sale of a security; (4) reliance upon the misrepresentation or omission; (5) economic loss; and (6) loss causation.”)
[6] In re Medimmune, Inc. Sec. Litig., 873 F.Supp. 953, 965 (D. Md. 1995). The biological product at issue in this case was Respivir, a polyclonal antibody product, which “significantly” reduced frequency of hospitalization for respiratory syncytial virus (RSV). Plaintiffs alleged “flaws” in study design, but the trial court appeared to interpret the statistical significance to mean that Respivir was “unquestionably efficacious.” Id. at 967.
[7] See, e.g., Padnes v. Scios Nova Inc., No. C 95-1693 MHP, 1996 WL 539711, at *5 (N.D. Cal. Sept. 18, 1996) (Patel, J.)[cited herein as Padnes]. See also DeMarco v. DePoTech Corp., 149 F.Supp. 2d 1212, 1225 (S.D. Cal. 2001)(“Although plaintiffs have established a legitimate difference in opinion as to the proper statistical analysis, they have hardly stated a securities fraud claim.”); n re Aldor Corp. Sec. Litig., 616 F.Supp. 2d 551, 568 n.15 (E.D. Pa. 2009) (allegations as to how data should have been analyzed do not support claims for false or misleading statements).
[8] Padnes at *2.
[9] Id. at *10.
[10] 2005 WL 4161977 (D. Colo. Oct. 20, 2005).
[11] Id. at *1.
[12] Id. at *6-7.
[13] Id. at *11.
[14] 2010 WL 8816155 (N.D. Cal. Aug. 24, 2010).
[15] 697 F.3d 869, 877 (9th Cir. 2012) (internal citations omitted), aff’g 2010 WL 8816155 (N.D. Cal. Aug. 24, 2010).
[16] Id. at 877-78.
[17] Id. at 878.
[18] Id. (“Because there are many ways to statistically analyze data, it is necessary to choose the statistical methodology before seeing the data that is collected during the trial; otherwise someone can manipulate the unblinded data to obtain a favorable result.”), citing and attempting to distinguish United States v. Harkonen, 2010 WL 2985257, at *4 (N.D. Cal. July 27, 2010).
[19] 706 F.3d 145 (2d Cir. 2013).
[20] Id. at 149.
[21] Id. at 149-50 (also noting that the press release provided a “preliminary analysis,” which might be less favorable upon further analysis).
[22] Id. at 150.
[23] Id. at 154-55 & 155n.11 (citing and quoting FDA Center for Drug Evaluation and Research: E9 Statistical Principles for Clinical Trials, 63 Fed. Reg. 49583, 49595 (Sept. 16, 1998), that post-hoc analyses are exploratory and “unlikely” to be accepted as support of efficacy.)
[24] United States v. Harkonen, 2010 WL 2985257 (N.D. Calif. 2010) ((Patel, J.) (denying defendant’s post–trial motions to dismiss the indictment, for acquittal, or for a new trial). Sometimes judges are looking for bright lines in the wrong places).
[25] 21 U.S.C. §§ 331(k), 333(a)(2), 352(a).
[26] 18 U.S.C. § 1343.
[27] United States v. Harkonen, 2010 WL 2985257, at *5 (N.D. Calif. 2010).
[28] United States v. Harkonen, 2013 WL 782354 (9th Cir. 2013).
[29] In re Actimmune Marketing Litig., 2010 WL 3463491 (N.D. Cal. Sept. 1, 2010), aff’d, 464 Fed.Appx. 651 (9th Cir. 2011).
[30] 131 S. Ct. 1309 (2011).
[31] Brief for the United States as Amicus Curiae Supporting Respondents, in Matrixx Initiatives, Inc. v. Siracusano, 2010 WL 4624148, at *14 (Nov. 12, 2010).
[32] Dr. Harkonen is expected to petition the Supreme Court for certiorari on statutory and constitutional grounds. See Alex Kozinski & Stuart Banner, “Who’s Afraid of Commercial Speech?” 76 VA. L. REV. 627, 635 (1990) (“[T]here are many varieties of noncommercial speech that are just as objective as paradigmatic commercial speech and yet receive full first amendment protection. Scientific speech is the most obvious; much scientific expression can easily be labeled true or false, but we would be shocked at the suggestion that it is therefore entitled to a lesser degree of protection. If you want, you can proclaim that the sun revolves around the earth, that the earth is flat, that there is no such thing as nitrogen, that flounder smoke cigars, that you have fused atomic nuclei in your bathtub — you can spout any nonsense you want, and the government can’t stop you.”).
