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Founded Year

2007

Stage

Acquired | Acquired

Total Raised

$116M

Valuation

$0000 

About IVERIC Bio

IVERIC Bio (NASDAQ: ISEE) is a biopharmaceutical company that focuses on the discovery and development of novel treatment options for retinal diseases with significant unmet medical needs. It develops both therapeutic product candidates for age-related retinal diseases and gene therapy product candidates for orphan Inherited Retinal Diseases (IRDs). It was formerly known as Ophthotech. The company was founded in 2007 and is based in New York, New York.

Headquarters Location

One Penn Plaza Suite 3520

New York, New York, 10119,

United States

212-845-8200

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IVERIC Bio Patents

IVERIC Bio has filed 26 patents.

The 3 most popular patent topics include:

  • disorders of choroid and retina
  • diseases of the eye and adnexa
  • ophthalmology
patents chart

Application Date

Grant Date

Title

Related Topics

Status

11/16/2018

3/7/2023

Disorders of choroid and retina, Diseases of the eye and adnexa, Complement system, Rare diseases, Ophthalmology

Grant

Application Date

11/16/2018

Grant Date

3/7/2023

Title

Related Topics

Disorders of choroid and retina, Diseases of the eye and adnexa, Complement system, Rare diseases, Ophthalmology

Status

Grant

Latest IVERIC Bio News

The ophthalmologist’s guide to evaluating the certainty of evidence using the GRADE approach

Feb 5, 2024

Evidence-based medicine demands knowledge of the best available research evidence to guide clinical decisions, which most often comes from rigorous systematic reviews and meta-analyses that identify, summarize, pool, and appraise all research evidence addressing a particular research question. While results from individual studies may appear impressive, our confidence in the body of evidence may be undermined by issues such as limitations in study designs or differences between the questions addressed in studies and the question of interest. To address such challenges, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group developed a system to evaluate the certainty (quality) of evidence—called GRADE. The GRADE approach intends to improve interpretation of evidence for decision-making [ 1 ]. The GRADE approach is applied to a body of evidence. A body of evidence refers to all research studies addressing a particular clinical question summarized in a systematic review and meta-analysis. According to the GRADE approach, the certainty of a body of evidence may be rated either as high, moderate, low, or very low (Fig. 1 ). High certainty evidence suggests that the estimated effect (the results from a rigorous systematic review and meta-analysis) is likely close to the true effect. Conversely, low or very low certainty evidence suggests that the estimated effect may in fact be substantially different from the true effect. Fig. 1: GRADE Approach. Original GRADE guidance proposed that for questions of causal inference, a body of evidence comprised of randomized trials starts at high certainty and non-randomized studies start at low certainty [ 2 ]. This is because, randomized trials, by virtue of randomization, achieve balance (more or less) in prognostic factors such that any observed differences in outcomes between randomized arms can be confidently attributed to the intervention under investigation. In non-randomized studies, however, participants with and without an exposure may differ with regard to prognostic factors such that any differences in outcomes between participants may be an artifact of differences in other prognostic factors. Even if investigators use sophisticated design and analytic methods to adjust for a comprehensive list of prognostic factors, important factors that are unknown or unmeasured may still influence results. This phenomenon is called residual confounding and is the reason why non-randomized studies are initially rated at low certainty. Newer GRADE guidance now suggests that a body of evidence comprised of non-randomized studies can also start at high certainty and the certainty of evidence may be downgraded by considering limitations of the evidence in comparison to a “target trial”—a hypothetical trial, without any limitations, that may or may not be feasible, addressing the question of interest [ 3 ]. Using this approach however, a body of evidence comprised of non-randomized studies will almost always still land at low or very low certainty due to concerns with residual confounding. The certainty of a body of evidence may be rated down by one or more levels due to concerns related to five factors: risk of bias (i.e., study limitations that may lead to systematic under- or over-estimation) [ 4 ], inconsistency (i.e., unexplained heterogeneity in results across studies) [ 5 ], indirectness (i.e., differences between the questions addressed in studies and the question of interest) [ 6 ], imprecision (i.e., the magnitude of confidence intervals around an estimate in relation to the minimum difference in the outcome that patients find important) [ 7 ], and publication bias (i.e., the tendency for studies with statistically significant results or positive results to be published, published faster, or published in journals with higher visibility) [ 8 ]. The certainty of evidence may also be rated up in select rare scenarios: when there is a dose-response relationship, a large effect, or when all plausible confounders act in the opposite direction than the observed effect [ 9 ]. GRADE is sometimes misinterpreted as evaluating risk of bias or misused as a risk of bias tool. GRADE, however, considers many factors beyond risk of bias and is intended to be applied alongside, rather than instead of, a risk of bias tool [ 4 ]. Systematic reviewers are expected to first assess the risk of bias of individual studies using an established risk of bias tool. Then, when applying GRADE, they should consider the risk of bias ratings of individual studies to make judgments about the risk of bias of the entire body of evidence. Of course, to apply GRADE, reviewers will also need to consider factors beyond risk of bias as described above. Fig. 2: Macular Hole Closure Meta-Analysis Results. Meta-analysis comparing macular hole closure between face-down positioning and control. Box 1: Application of GRADE to a systematic review in ophthalmology A systematic review and meta-analysis of randomized trials investigated the effects of face-down positioning following full-thickness macular hole surgery [ 10 ]. The systematic review investigated the proportion of patients with macular hole closure following surgery. The review identified eight trials that reported on macular hole closure. It used the RoB 2.0 tool to assess risk of bias [ 11 ]. For this outcome, the majority of evidence came from trials rated at low risk of bias. Figure  2 summarizes the results of the meta-analysis. The meta-analysis yields a relative risk of 1.05 (95% CI: 0.99 to 1.12). The application of the GRADE approach to binary outcomes requires consideration of absolute effects (e.g., risk differences) [ 12 ]. Fortunately, relative effects obtained from meta-analyses like relative risks and odds ratios can be transformed to absolute effects [ 13 ]. 86.9% of patients without face-down positioning experience macular hole closure. Using the relative risk obtained from the meta-analysis, this translates to an absolute risk of 912 in 1000 patients with face-down positioning (95% CI: 860 to 973) or a risk difference of 43 more (95% CI: 9 fewer to 104 more). The systematic review authors rated the certainty of the body of evidence as low. The body of evidence is comprised of randomized trials. The investigators downgraded the certainty of evidence by one level for imprecision because the lower and upper bounds of the confidence intervals suggest opposing clinical actions. The lower bound of the confidence interval (9 fewer cases of macular hole closure in 1000 patients) suggests that face-down positioning has little or no effect on macular hole closures. Conversely, the upper bound of the confidence interval (104 more cases of macular hole closure in 1000 patients) suggests that face-down positioning may importantly increase the proportion of patients with macular hole closure. The investigators also downgraded the certainty of evidence by one level for inconsistency. Whether the effect estimates were sufficiently inconsistent to warrant rating down for inconsistency is subjective. Some may argue that the confidence intervals and point estimates are sufficiently similar to forego rating down for inconsistency. If the investigators were interested in whether the effect estimate is within a narrow range, then rating down for inconsistency would be justifiable. The investigators suggested that rating down for inconsistency was a borderline decision and that they were also concerned about potential indirectness because it was unclear whether the effect of face-down positioning is consistent across other surgical factors, such as peeling of the internal limiting membrane, type of gas, size of the internal limiting membrane peel, and duration of face-down positioning. The final rating of the certainty of evidence is thus low, suggesting that face-down positioning may increase the risk of macular hole closures. The review also judged other outcomes (visual acuity and complications) as low certainty. Low certainty evidence suggests that the true effect may be different from the estimated effect and that new evidence may importantly change the effect estimate. Updates The GRADE Working Group has refined and updated its guidance since its inception. Official guidance from the GRADE Working Group is summarized in GRADE Guidance Papers, while GRADE Concept Papers and GRADE Notes discuss concepts relevant to GRADE and case studies [ 14 ]. While theoretically anyone can use the GRADE approach to evaluate the certainty of a body of evidence, the confident application of the GRADE approach will require familiarity with the prodigious volume of GRADE guidance papers. Initially, GRADE guidance focused on assessing the certainty of evidence for causal questions. Since then, GRADE guidance has been extended to apply to questions of prognosis [ 15 ] and diagnosis [ 16 ]. GRADE now also offers guidance for evaluating the certainty of evidence from network meta-analyses [ 17 , 18 ]. GRADE has recently clarified judgments related to imprecision [ 19 ]. Newer GRADE guidance emphasizes that the certainty of evidence represents the certainty that the true effect lies on one side of a specified threshold or within a chosen range [ 19 ]. Most recently, GRADE has been expanded to offer guidance on moving from evidence to recommendations, by way of GRADE Evidence-to-Decision frameworks [ 20 ]. These frameworks provide a structured process for moving from evidence to guideline recommendations, systematically considering all factors that may bear on the direction and strength of the recommendations, including the balance between benefits and harms, certainty of evidence, values and preferences, and sometimes, cost-effectiveness, acceptability, feasibility, and equity. GRADE also offers guidance on summarizing results, developed based on feedback from evidence users and other stakeholders [ 21 ]. According to this guidance, high certainty evidence is described with declarative statements, moderate certainty evidence with ‘probably’, low certainty evidence with ‘may’ and very low indicated with ‘very uncertain’. Advantages of the GRADE approach GRADE has now been adopted by over 100 organizations worldwide, including the World Health Organization, the National Institute for Health and Care Excellence, and the Cochrane Collaboration, and across a diverse range of health fields [ 22 ]. The GRADE approach offers a systematic and transparent process for assessing the certainty of evidence and moving from evidence to recommendations. Its application ensures that all factors that may bear on the certainty of evidence or on the direction and strength of recommendations are systematically and transparently considered. Nevertheless, its application invariably involves subjective judgments and such judgments may vary between reviewers, guideline developers, and other decision-makers. Disagreements between reasonable individuals are expected. The transparency facilitated by GRADE, however, allows parties to identify specific sources of disagreement. The application of GRADE also promotes the consideration of patient values and preferences. According to the GRADE approach, patient perspectives inform the selection of outcomes for consideration for guideline recommendations and other decisions, whether the benefits of a particular course of action outweigh harms, and the minimum important difference in outcomes that patients find important [ 23 ]. Considering values and preferences respects the rights of citizens to participate in health decision-making, aligns guidelines with the needs and priorities of the communities they are intended to serve, ensures recommendations are logistically feasible and acceptable, and improves support for the recommendations [ 24 , 25 ]. Conclusion GRADE presents a systematic and transparent approach to evaluating the certainty of evidence and for moving from evidence to recommendations. It has been adopted by multiple authoritative international organizations. Since its inception, GRADE has been refined and updated and will likely continue to evolve based on the experiences of reviewers and guideline developers. Its application offers several strong advantages, including the promotion of consistency in standards to evaluate evidence across health fields and explicit consideration of patient values and preferences. References Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6. Schünemann HJ, Cuello C, Akl EA, Mustafa RA, Meerpohl JJ, Thayer K, et al. GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence. J Clin Epidemiol. 2019;111:105–14. Brozek JL, Akl EA, Jaeschke R, Lang DM, Bossuyt P, Glasziou P, et al. Grading quality of evidence and strength of recommendations in clinical practice guidelines: Part 2 of 3. The GRADE approach to grading quality of evidence about diagnostic tests and strategies. Allergy. 2009;64:1109–16. Dena Zeraatkar Dena Zeraatkar, Mark Phillips, Mohit Bhandari, Varun Chaudhary & Lehana Thabane Division of Respirology, Department of Medicine, University of Toronto, Toronto, ON, Canada Tyler Pitre David H. Steel David H. Steel Charles C. Wykoff Charles C. Wykoff Tien Yin Wong Tien Yin Wong Tien Yin Wong & Tien Y. Wong Department of Surgery, McMaster University, Hamilton, ON, Canada Mohit Bhandari & Varun Chaudhary Sobha Sivaprasad Peter Kaiser David Sarraf Sophie J. Bakri Sunir J. Garg Rishi P. Singh Rishi P. Singh Frank G. Holz Tien Y. Wong Robyn H. Guymer Robyn H. Guymer SriniVas R. Sadda SriniVas R. Sadda Tyler Pitre Mark Phillips David H. Steel Charles C. Wykoff Tien Yin Wong Mohit Bhandari Varun Chaudhary COMPETING INTERESTS DHS: Consultant: Gyroscope, Roche, Alcon, BVI; Research Funding: Alcon, Bayer, DORC, Gyrsocope, Boehringer-Ingelheim. CCW: Consultant: Acuela, Adverum Biotechnologies, Inc, Aerpio, Alimera Sciences, Allegro Ophthalmics, LLC, Allergan, Apellis Pharmaceuticals, Bayer AG, Chengdu Kanghong Pharmaceuticals Group Co, Ltd, Clearside Biomedical, DORC (Dutch Ophthalmic Research Center), EyePoint Pharmaceuticals, Gentech/Roche, GyroscopeTx, IVERIC bio, Kodiak Sciences Inc, Novartis AG, ONL Therapeutics, Oxurion NV, PolyPhotonix, Recens Medical, Regeron Pharmaceuticals, Inc, REGENXBIO Inc, Santen Pharmaceutical Co, Ltd, and Takeda Pharmaceutical Company Limited; Research funds: Adverum Biotechnologies, Inc, Aerie Pharmaceuticals, Inc, Aerpio, Alimera Sciences, Allergan, Apellis Pharmaceuticals, Chengdu Kanghong Pharmaceutical Group Co, Ltd, Clearside Biomedical, Gemini Therapeutics, Genentech/Roche, Graybug Vision, Inc, GyroscopeTx, Ionis Pharmaceuticals, IVERIC bio, Kodiak Sciences Inc, Neurotech LLC, Novartis AG, Opthea, Outlook Therapeutics, Inc, Recens Medical, Regeneron Pharmaceuticals, Inc, REGENXBIO Inc, Samsung Pharm Co, Ltd, Santen Pharmaceutical Co, Ltd, and Xbrane Biopharma AB. TYW: Consultant: Aldropika Therapeutics, Bayer, Boehringer Ingelheim, Genentech, Iveric Bio, Novartis, Plano, Oxurion, Roche, Sanofi, and Shanghai Henlius; Research funding: National Key R&D Program, China (grant number 2022YFC2502800); Investor, patent holder, and cofounder of the start-up companies EyRiS and Visre. MB: Research funding: Pendopharm, Bioventus, Acumed. VC: Advisory Board Member: Alcon, Roche, Bayer, Novartis; Grants: Bayer, Novartis – unrelated to this study. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions

IVERIC Bio Frequently Asked Questions (FAQ)

  • When was IVERIC Bio founded?

    IVERIC Bio was founded in 2007.

  • Where is IVERIC Bio's headquarters?

    IVERIC Bio's headquarters is located at One Penn Plaza, New York.

  • What is IVERIC Bio's latest funding round?

    IVERIC Bio's latest funding round is Acquired.

  • How much did IVERIC Bio raise?

    IVERIC Bio raised a total of $116M.

  • Who are the investors of IVERIC Bio?

    Investors of IVERIC Bio include Astellas Pharma, Novo Holdings, HBM Healthcare Investments, SV Health Investors and Clarus.

  • Who are IVERIC Bio's competitors?

    Competitors of IVERIC Bio include Neuronascent, Adamas Pharmaceuticals, CoMentis, Hyperion Therapeutics, iPierian and 7 more.

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