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Category: News

How We Built a Human Protein Library for Biotherapeutic Safety Screening

In this article:

This article is part 7 of a series about specificity testing. Be sure to read part 6, about the consequences of off-target binding.

Summary

Specificity testing is ultimately a patient safety question: does this antibody bind only what it’s supposed to? Answering it requires a library that represents the human proteins a biotherapeutic will encounter in vivo, in their biologically relevant conformations. The Membrane Proteome Array (MPA) library was purpose-built to do exactly that. Anchored in FDA guidance and built through deliberate design choices, it captures roughly 6,000 membrane proteins — canonical and non-canonical, sex-balanced, developmentally diverse — representing 94% of the human membrane proteome.

How was the MPA library designed?

Earlier articles in this series established that off-target binding is consequential, common, and frequently missed by traditional specificity testing methods. The Membrane Proteome Array (MPA) was designed to address that gap. Here, we look at the foundation of the platform: the membrane protein library.

In developing the membrane protein library, we began with the FDA’s 1997 Points to Consider in the Manufacture and Testing of Monoclonal Antibody Products for Human Use, which named 34 normal adult human tissues that should be evaluated for off-target binding. These 34 tissues span the major systems of the human body, representing the regions a biotherapeutic is most likely to encounter as it circulates through a patient.

Tissue cross-reactivity (TCR) studies address this FDA guidance by staining tissue sections from these organs. The MPA was designed to satisfy it differently. It individually expresses nearly every membrane protein present in those 34 tissues in whole cells, where each protein adopts its native conformation. The MPA not only delivers the same anatomical scope as TCR, it also identifies specific target and off-target proteins — something tissue-based methods cannot do.

TK
The MPA library includes membrane proteins from the 34 FDA-specified tissues. The proteins span the major systems of the human body, from the gastrointestinal and circulatory to the endocrine, respiratory, reproductive, and nervous systems.

 

To build the library, our team used a bioinformatics approach to identify all membrane proteins expressed in the 34 specified tissues, drawing on bulk RNA sequencing data, transmembrane topology prediction tools, and mass-spectrometry-derived cell surface protein databases. Full-length canonical isoforms were obtained from UniProt sequences. The result is a library of approximately 6,000 membrane proteins, representing 94% of the human membrane proteome. Importantly, this library spans the full functional range of membrane proteins. The next article in the series will discuss the secreted protein library, which together with the membrane protein library allows for screening across over 7,000 human proteins.

Bar chart showing the functional composition of the MPA library across categories including receptors, enzymes, transporters, ligands, and adhesion proteins.
Composition of the MPA protein library according to DAVID functional annotation categories. The MPA’s ~6,000 membrane proteins span the full range of cellular roles, from receptors and enzymes to transporters, adhesion molecules, and viral proteins.

What’s in the library beyond the canonical membrane proteome?

A bioinformatics scan of canonical transmembrane proteins captures the bulk of the membrane proteome, but not all of it. Several categories of proteins that matter for specificity testing could easily be missed by a standard search. The MPA library includes them, along with membrane proteins predicted to be intracellular. Here’s why.

Intracellular membrane proteins. The MPA library deliberately includes membrane proteins thought to localize inside the cell — on the nucleus, Golgi, endoplasmic reticulum, and other organelle membranes. There are two reasons. First, cellular localization is often a prediction, and it’s not fully known which membrane proteins traffic to the cell surface and which do not. Second, even when localization is well-characterized under one set of conditions, it can shift with cell type, activation state, or disease state.

Heterocomplexes. Some membrane proteins only express or fold properly as part of an obligate heteromer; integrins are the canonical example. The MPA library contains approximately 250 heterocomplexes, generally composed of two or three subunits or featuring subunits that participate in multiple complexes. Monomeric subunits of each heterocomplex are also included individually. Because the MPA expresses each protein in a human or other eukaryotic cell, heterocomplexes can also form naturally with the cell’s endogenous proteins.

GPI-linked proteins. Glycosylphosphatidylinositol-linked proteins are anchored to the cell membrane but lack transmembrane domains, which means a standard bioinformatics search targeting canonical transmembrane topology would miss them. Given their importance and surface expression, GPI-linked proteins were curated separately from UniProt. The MPA library includes 120 GPI-linked proteins.

Viral envelope proteins. These are not human proteins and would not be captured by an analysis of the human genome. But they’re important for biotherapeutic development, particularly for antiviral therapies. The MPA library includes 35 envelope proteins from viruses including HIV, dengue, and Ebola.

How well does the MPA represent human variation?

A library can be large without being broadly representative. A specificity testing tool intended to support patient safety needs to address coverage across the dimensions that matter for actual patient populations: protein isoforms, human populations, biological sex, and developmental stages.

The MPA library represents protein isoforms, human populations, biological sex, and developmental stages.
The MPA library is designed for breadth of representation across the dimensions that matter for patient populations.

 

Protein isoforms. The total number of human protein variations, across splice isoforms and post-translational modifications, is beyond the capability of any single in vitro test system. The MPA library is built from canonical isoforms (UniProt), which contain the full target protein sequence; non-canonical isoforms typically delete exons. The library therefore represents the major haplotype and the most complete target sequence for testing binding. Specific isoforms, polymorphisms, or mutations relevant to a particular patient population may need to be evaluated outside of the standard MPA study.

Human population coverage. The MPA is designed for specificity testing across all human populations. The library uses the GRCh38 reference assembly’s canonically defined isoforms. While genetic variation accounts for some differences among humans, gene expression rather than protein sequence is believed to drive most phenotypic diversity across populations (Taylor et al., 2024). Because protein-coding sequences are mostly identical across populations and the MPA overexpresses full-length proteins, the library captures nearly all potential binding targets across human genetic backgrounds. We do note that GRCh38 is skewed toward European and African ethnicities, and the library does not represent disease-specific mutations.

Sex differences. The MPA library is unbiased toward biological sex. Using the Human Protein Atlas, we identified 57 transmembrane proteins with enriched expression in male- or female-specific tissues, nearly all of which are included in the MPA library. We also identified genes on the Y chromosome encoding transmembrane proteins, 10 in total, all of which are included in the MPA library.

Developmental stages. Consistent with the FDA’s TCR panel recommendation, the MPA is designed to represent the adult membrane proteome. However, the library also includes nearly all membrane proteins expressed in the placenta and the fetus, which can be exposed to therapeutics intended for the mother. These inclusions make the MPA better than tissue-based methods for testing binding against developmentally restricted proteins, and eliminate the need to procure fetal tissues.

The breadth of coverage represented in the MPA library is structurally difficult to achieve with tissue-based methods. As discussed earlier in the series, tissue cross-reactivity (TCR) studies draw from a small donor panel, limiting the genetic diversity captured in the study. By working at the protein level and drawing from the reference genome, the MPA library represents the human proteome rather than the biology of a specific set of donors.

Looking ahead

The MPA library is engineered for comprehensive coverage of the membrane proteome — but membrane proteins aren’t the whole specificity story. Secreted proteins can also be off-target binders, with consequences for both safety and pharmacokinetics. In the next article, we’ll look at the Secreted Proteome Library (SPL), which extends the same engineering philosophy to soluble proteins and gives developers a complete picture of their molecule’s interactions across the human proteome.

Integral Molecular Earns Back-to-Back Top Workplace Honors from The Philadelphia Inquirer

Philadelphia – Integral Molecular, a founding member of Philadelphia’s biotechnology community, has again been named a Top Workplace by The Philadelphia Inquirer. The honor is based entirely on confidential employee feedback and measured against national workplace benchmarks.

See the complete list of Top Workplaces named by the Philadelphia Inquirer

“We are incredibly proud to be recognized once again as a Top Workplace,” said Sharon Willis, PhD, Co-founder of Integral Molecular. “This award reflects our commitment to scientific excellence, collaboration, and innovation, as well as the strong sense of community we’ve built. As we grow, we remain focused on fostering an environment where our team can thrive, contribute meaningfully, and advance work that improves human health.”

Integral Molecular is proud of a culture built on:

  • Scientific Excellence: Curiosity and collaboration enable our scientists to combine deep expertise, cutting-edge technologies, and creative problem-solving to tackle complex biological challenges, develop innovative solutions, and advance the discovery of new therapies.
  • Employee Development and a People-First Culture: A supportive environment where employees are encouraged to grow professionally, collaborate across teams, and celebrate shared successes.
  • Community Partnerships: Strong relationships with local educational institutions and workforce development organizations that help recruit, train, and retain homegrown talent.
  • Biotechnology Leadership: Active participation in regional initiatives that strengthen Pennsylvania’s life sciences ecosystem and support continued industry growth.

Learn more about Integral Molecular and view current career opportunities.

About Integral Molecular
Integral Molecular is the industry leader in developing innovative technologies that advance the discovery of antibody therapeutics against difficult protein targets. With 25 years of experience focused on membrane proteins, viruses, and antibodies, Integral Molecular’s technologies have been integrated into the drug discovery pipelines of over 600 biotech and pharmaceutical companies to help discover new therapies for cancer, diabetes, autoimmune disorders, and viral threats such as SARS-CoV-2, Ebola, Zika, and dengue viruses.

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Press Contact:
Integral Molecular
Soma Banik, PhD
Director of Public Relations
215-966-6061
info@integralmolecular.com

The Consequences of Off-Target Binding Are Real. So Are the Solutions.

In this article:

This article is part 6 of a series about specificity testing.

Summary

Off-target binding doesn’t always cause harm—but when it goes undetected, the consequences can be serious. Published case studies document off-target interactions that caused adverse events in clinical trials, halted drug development programs, and may explain the known safety profiles of approved therapeutics. These cases also demonstrate that when off-targets are identified early, solutions exist: engineering fixes, informed go/no-go decisions, and cleaner IND filings.

Can off-target binding cause adverse events?

In the previous article, we looked at how common off-target binding is among biotherapeutic drug candidates. Here, we look at what undetected off-target binding can mean in practice.

One of the most well-documented examples of off-target-driven toxicity involves camrelizumab, an anti-PD1 monoclonal antibody developed for cancer immunotherapy. During Phase 1 clinical trials, a majority of treated patients developed severe capillary hemangioma. These abnormal blood vessel growths had no obvious connection to PD1, the antibody’s intended target (Mo et al., 2018).

Retrospective screening of camrelizumab using a cell-based protein array identified the source of the problem: the antibody was also binding VEGFR2, a receptor with a central role in blood vessel formation (Finlay et al., 2019). And the binding wasn’t passive. Camrelizumab acted as an agonist, actively stimulating VEGFR2 to promote vascular neogenesis, which, in vivo, leads to hemangioma.

The causal link was confirmed when patients treated with a VEGFR2 antagonist saw the hemangioma effects resolved (Li et al., 2019). Equally significant: CDR mutagenesis abolished binding to VEGFR2 while preserving high affinity for PD1 (Finlay et al., 2019). Had it been found earlier, the off-target binding could have been engineered away prior to trials in patients.

Timeline of the camrelizumab story, from problem to diagnosis, CDR engineering, and resolution.

What does MPA screening of clinical-stage MAbs reveal?

Looking more broadly, Membrane Proteome Array (MPA) screening of clinical-stage monoclonal antibodies has identified several cases where off-target binding may explain known adverse events (Norden et al., 2024). Among them:

  • A clinical-stage MAb armed with a toxic payload was found to bind an off-target protein with widespread tissue expression—a combination predicted to cause significant toxicity.
  • A MAb that was withdrawn from clinical trials due to severe patient adverse events was found to bind an unrelated membrane protein even more strongly than its intended target.

In these cases, the relationship between the off-target interaction and the observed clinical outcome is not fully established. What is clear is that the off-target binding existed, went undetected by prior specificity assessments, and was later identified by MPA screening.

Can secreted protein off-targets pose safety and efficacy risks?

Membrane proteins are the primary focus for specificity testing because off-target binding to them carries the highest safety risk, but off-target binding to secreted proteins can also carry consequences. While off-target binding to secreted proteins is less likely to cause cell death or direct disruption of cell biology, toxicity has still been reported.

In one case, development of ABT-736, an anti-beta-amyloid antibody, was discontinued after it caused severe toxicity in cynomolgus monkeys. This toxicity was later traced to off-target binding to platelet factor 4, a secreted plasma protein (Loberg et al., 2021).

Beyond direct toxicity, off-target binding to abundant circulating proteins can also affect pharmacokinetics and dosing (Bumbaca et al., 2011).

To identify potential secreted off-targets, and to provide a comprehensive picture of your molecule’s interactions with the human body, Integral Molecular offers screening against over 1,200 soluble proteins on the Secreted Proteome Library (SPL). We’ll share more about the SPL in a future article.

Do off-targets always cause adverse events?

The camrelizumab story could have gone very differently if the VEGFR2 interaction had been identified preclinically. CDR mutagenesis, the same approach that was used retrospectively, could have been applied before patients were enrolled.

This is what earlier, more comprehensive specificity testing enables: not just detection of off-targets, but the opportunity to act on that information while options still exist. For candidates without off-target interactions, MPA results can be included directly in IND filings. For candidates with off-target interactions, the MPA identifies the specific protein involved, enabling a focused investigation rather than a search for an unknown cause. While off-target binding does not always lead to adverse events, it does always warrant investigation.

Any investigation into an off-target should consider factors including the relative strength of the off-target interaction compared to on-target binding, the epitope location and accessibility of the off-target protein, and the therapeutic mechanism of action. Integral Molecular’s Enhanced Binding Analysis service provides the quantitative data needed to begin that evaluation.

Understanding these factors will help you understand the associated risk and arm you with the information you need to make decisions. For example, a low-affinity interaction with an intracellular epitope presents a very different risk profile than strong binding to a widely expressed cell-surface protein—particularly for cell-killing modalities like ADCs or CAR-T therapies.

Enhanced Binding Analysis performs a statistical assessment, measures relative binding strength, and evaluates epitope accessibility.
Enhanced Binding Analysis provides information about target binding, accessibility, and potential for therapeutic toxicity.

Looking ahead

In the next article, we’ll cover how the MPA library was designed, and what it means for a specificity testing tool to be truly comprehensive.

1 in 3 Antibody Drug Candidates Bind Off-Targets. Here’s What That Means.

In this article:

This article is part 5 of a series about specificity testing. Be sure to read part 3, about the limitations of tissue cross-reactivity studies. 

Summary

Off-target binding in antibody therapeutics is far more common than most people expect. Our analysis of hundreds of antibody-based drug candidates found that roughly 1 in 3 lead candidates display polyspecific off-target binding. And the problem persists as drugs advance through development. Even among FDA-approved MAbs, about 15% show off-target binding. Side-by-side comparisons of MPA and tissue cross-reactivity (TCR) data reveal that many of these off-targets went undetected by traditional methods. Spotting these interactions early, and identifying the specific off-target proteins, is the first step toward addressing them.

How common is off-target binding, really?

In an earlier article, we mentioned that 1 in 3 antibody lead candidates has off-target binding. Here, we’ll dig into that number.

To quantify the prevalence of polyspecificity across the industry, we conducted a retrospective analysis of all antibody-based therapeutics submitted by customers for specificity testing on the Membrane Proteome Array (MPA) over a defined time period. We analyzed 254 samples in total, including MAbs, scFv-Fcs, and VHH-Fcs. These samples primarily represent lead candidates at biopharmaceutical companies throughout the industry. To be included in the analysis, each sample had to have successfully completed all three steps of the MPA process: Assay Setup, MPA Screen, and Validation (Norden et al., 2024).

The results were striking:

  • 83 of 254 samples (32.7%) displayed polyspecific off-target binding.
  • Among the polyspecific antibodies, about half had a single off-target, while the rest had two or more.
  • Off-target binding was almost always to completely unpredictable membrane proteins with no significant sequence homology to the intended target.

Graph of total molecules tested over time x number of monospecific and polyspecific molecules reveals that 33% of test articles are polyspecific. Pie graph shows that of this 33%, 16% have one off-target, 8% have 2, and 9% have 3 or more.

33% of 254 antibody-based lead candidates screened on the MPA demonstrated validated off-target binding. Data from Norden et al., 2024.

The 33% figure reflects true, confirmed off-target binding interactions. Off-target binding was detected during MPA screening on ~6,000 native membrane proteins, then validated by antibody titration studies to confirm each hit. Note that these results include only CDR-mediated interactions. Non-CDR-mediated interactions, such as binding to Fc receptors or lectins, would push the off-target rate even higher if counted.

Perhaps most importantly, the off-targets were almost never related to the intended targets. In part, that’s because most MAbs screened on the MPA have already been tested against members of the same protein family. The study results represent genuinely unexpected interactions that conventional approaches would miss entirely.

The findings support our recommendation to conduct specificity testing using cell-based protein arrays early in drug development, ideally during lead selection, when potential toxicity issues can be identified and addressed with relatively little impact on a drug program.

Does polyspecificity persist into late-stage development?

Given the high off-target rate among lead candidates, we wanted to know whether polyspecificity persists among MAbs that have gone into humans. To find out, we produced biosimilars of 83 clinical-stage, FDA-approved, and withdrawn MAbs and screened them on the Membrane Proteome Array (MPA).

The answer is yes: polyspecificity persists at every stage of clinical development.

  • 18.1% of clinical MAbs overall showed off-target binding.
  • Off-target rates were slightly higher for withdrawn MAbs (22.2%) and those in Phase 2/3 (20.0%) compared to approved MAbs (15.0%).

Clinical MAbs screened on the MPA. Table with number of antibodies, number of off-targets, and off-target rate by status: withdrawn, phase 2/3, FDA-approved, and total

Off-target binding was found in MAbs at all stages of clinical development, with higher rates among withdrawn and clinical-stage MAbs than approved ones. Based on Norden et al., 2024.

The lower rate among clinical-stage MAbs compared to lead candidates (18% vs. 33%) suggests that polyspecificity contributes to drug attrition; candidates with off-target binding appear to drop out of the pipeline at higher rates. But an off-target binding rate of 15% in FDA-approved drugs makes clear that current screening methods are not catching everything.

An independent analysis published in 2026 reached a similar conclusion. Dai et al. used a different platform to screen 174 FDA-approved and clinical-stage MAbs against 6,172 human extracellular proteins, finding that 28% had at least one off-target. The Dai et al. and Norden et al. studies used different technologies and somewhat different protein sets, but both point to the same conclusion: off-target binding among clinical antibodies is not rare, and it is not an artifact of any single platform.

Why can’t you predict off-target binding from sequence analysis alone?

One of the most consistent findings across our Membrane Proteome Array (MPA) data is that off-target binding is almost never to a related protein. So why is it happening?

Three mechanisms have been identified:

Molecular mimicry is likely the most common. Critical epitope residues in the intended target are mirrored, by chance, in a completely unrelated protein. In one well-documented example, a MAb we isolated against the glucose transporter SLC2A4 (GLUT4) also bound to Notch1, a signaling protein with less than 7% sequence identity and no structural similarity to GLUT4. Epitope mapping traced the cross-reactivity to a shared LGXXGP motif present in both proteins: one in a loop on GLUT4, the other in a disulfide-constrained loop on Notch1 (Tucker et al., 2018).

In an example of molecular mimicry, the target and a completely unrelated off-target share an LGXXGP epitope

Molecular mimicry explains how a MAb against SLC2A4 (GLUT4) also bound Notch1—despite less than 7% sequence identity. Epitope mapping revealed that both proteins share an LGXXGP epitope motif. Graphic based on Norden et al., 2024, Fig. 6.

CDR plasticity is a second mechanism, in which conformational flexibility in the antibody’s complementarity-determining regions (CDRs) allows the paratope to adapt to more than one antigen.
Differential CDR engagement is a third possibility: off-target binding may occur through entirely different CDR residues than those used to bind the primary target.

The practical implication is the same regardless of mechanism: off-target binding cannot be reliably predicted from sequence or structural analysis. Proteome-wide empirical screening is the only reliable way to detect it.

What is TCR missing?

As discussed in an earlier article, tissue cross-reactivity (TCR) studies have significant limitations. Our own data provides direct evidence of one of the most consequential: TCR is missing off-target interactions that the Membrane Proteome Array (MPA) detects.

To compare the two approaches, we reproduced FDA-approved MAbs and screened them on the MPA, then compared our results to TCR data from the corresponding biologics license applications (BLAs). In several cases, the MPA identified off-target binding that was not mentioned in the TCR summaries.

MPA data plots for the three case studies described in the text, where TCR missed off-targets, off-targets were masked in TCR, and an off-target was buried amid TCR staining.

In three side-by-side comparisons, MPA screening of biosimilars of FDA-approved MAbs identified off-targets that were not detected or reported in available TCR data from BLA applications. Dotted line represents 3 SD above calculated background. Adapted from Norden et al., 2024.

Three examples illustrate the pattern:

  • Case Study 1. This antibody targets a plasma membrane protein expressed on lymphocytes. The MPA correctly identified the intended target—and also detected two off-target membrane proteins that bound even more strongly than the target. The BLA summary indicated TCR staining consistent with known target expression on lymphocytes, with no off-target binding reported.
  • Case Study 2. This antibody targets a membrane protein expressed on the plasma membrane and intracellularly in myeloid cells. The MPA identified the target and an additional off-target expressed on the same cell type. The BLA summary noted staining consistent with known target expression and did not mention off-target binding. When the target and off-target are co-expressed on the same cell, tissue-based methods cannot distinguish between them.
  • Case Study 3. This antibody targets a membrane protein with low, widespread expression across most normal tissues that is upregulated in certain disease states. The MPA identified the target and an off-target membrane protein. The BLA summary reported primarily cytoplasmic staining across many tissues, with no significant off-target concerns—likely because identifying an off-target signal against a background of widespread positive staining is extremely difficult using TCR.

In none of these cases were the off-targets members of the same protein family as the intended target. These represent genuinely unexpected interactions that TCR was not designed to detect.

Looking ahead

The data clearly show that off-target binding is a widespread problem that traditional methods are failing to catch. But what actually happens when those interactions go undetected—and make it into the clinic? In the next article, we examine case studies where undetected off-target binding led to serious adverse events in patients, and what those examples tell us about the need for better specificity testing. 

Webinar Presented by Integral Molecular and The Antibody Society – 100+ Undruggable Targets Unlocked Through Parallel MAb Engineering

Thursday, June 25, 2026
11 am EDT
View the recording

Many high value therapeutic targets, particularly multipass membrane proteins, remain untapped due to technical constraints such as sequence conservation and structural complexity. In this webinar, we will describe an accelerated pathway from discovery to preclinical candidate selection for these challenging targets. We will share key lessons learned from campaigns targeting more than 100 highly validated membrane protein targets that previously lacked antibodies, with insights for enabling target validation and preclinical candidate selection.

What You Will Learn:

  • How advanced discovery strategies have unlocked 100+ ‘undruggable’ targets.
    mRNA immunization, virus-like particles (VLPs), divergent avian host species, and other strategies have lowered the barriers to successful antibody generation against GPCRs, ion channels, and transporters involved in oncology, immune disorders, and metabolic disorders.
  • Parallel engineering combined with AI/ML provides a faster pathway to a preclinical candidate. Comprehensive experimental data from CDR-Scanning (Paratope-PLUS®) enables AI/ML to simultaneously optimize therapeutic candidates for affinity, specificity, NHP cross-reactivity, and developability. Comprehensive datasets also provide the basis for stronger antibody IP by providing enablement and written description for antibody genus claims.

 

View the recording

How Is the MPA Being Qualified by the FDA?

In this article: 

This article is part of a series about specificity testing. Be sure to read part 3, about the limitations of tissue cross-reactivity studies. 

Summary 

Tissue cross-reactivity (TCR) studies have served as the standard for specificity testing since the 1980s, but their limitations—inability to identify specific proteins, subjective interpretation, poor clinical correlation—have long been recognized. The Membrane Proteome Array (MPA) was designed to address these gaps with objective, quantitative data that identifies specific off-target proteins. In 2021, we began working with the FDA to qualify the MPA as a Drug Development Tool through the ISTAND program. While the FDA already accepts MPA data, this qualification process validates the scientific rigor behind the platform and helps formalize the shift toward more predictive, human-relevant specificity testing methods.

Why we built a better specificity testing tool

As discussed in the previous article, tissue cross-reactivity (TCR) studies leave significant gaps in our understanding of therapeutic specificity. Most critically, they can’t tell you which protein a therapeutic is binding to—only where unexpected staining appears in tissues. That makes it nearly impossible to assess the actual safety risk or design appropriate follow-up studies. 

Drug developers and regulators have long recognized the need for better tools. The FDA stated as far back as 1997 that “appropriate newer technologies should be employed as they become available and validated.” More recently, their 2024 CAR-T guidance specifically named “protein arrays” as an acceptable alternative to TCR. 

The Membrane Proteome Array (MPA) was designed to fill the gaps left by TCR. And the shift in the regulatory landscape has already begun: MPA data has already been accepted in over 100 IND applications. Proper specificity assessment early in development contributes to better candidate selection, more efficient regulatory review, safer clinical trials, and ultimately better therapeutics for patients. 

What advantages does the MPA have over conventional methods?

The MPA offers several key advantages over conventional specificity testing methods: 

      • Identifies specific proteins. When the MPA detects off-target binding, it tells you exactly which proteins are involved. That enables focused investigation into potential safety issues and informed decisions about whether to proceed with development. TCR studies, by contrast, can only show you tissue locations. 
      • Uses native protein conformations. Each protein is expressed in its natural state within whole eukaryotic cells, with proper folding, post-translational modifications, and membrane environment. TCR tissue processing can alter protein structures, potentially causing false positives or negatives.  
      • Eliminates donor variability. The MPA uses established cell lines with consistent handling protocols, so every protein is fully expressed and available for testing. TCR’s reliance on tissue samples from three individual donors means protein expression varies unpredictably. 
      • Provides objective, quantitative data. The MPA uses flow cytometry to generate measurements that can be statistically analyzed and compared across studies. This eliminates the subjectivity inherent in TCR, where pathologists score immunohistochemistry staining patterns.  

Additionally, MPA data supports regulatory submissions directly. MPA results provide the precise, quantitative data needed for IND applications. For candidates without off-targets, the specificity is demonstrated clearly. For those with off-targets, you have the molecular detail needed to design appropriate follow-up studies. 

These advantages made the MPA an ideal candidate for FDA qualification as a Drug Development Tool—a formal recognition that would help accelerate the broader shift toward more predictive specificity testing methods.

Specificity testing on the Membrane Proteome Array offers many advantages over tissue cross-reactivity studies.

What is the ISTAND qualification process?

In May 2021, Integral Molecular submitted a Letter of Intent to the FDA’s ISTAND program to qualify the MPA as a Drug Development Tool. ISTAND (Innovative Science and Technology Approaches for New Drugs) provides a pathway for qualifying novel methods that can improve drug development and regulatory review. 

The FDA accepted the MPA into ISTAND in July 2022, making it the first tool ever accepted into the program. This milestone reflected both the platform’s scientific merit and the FDA’s recognition that better specificity testing methods are needed. 

The qualification process involves several stages: 

      • Letter of Intent (LOI) - Describes the tool, its intended use, and preliminary data supporting its utility. Accepted July 2022. 
      • Qualification Plan (QP) - Outlines the validation studies, performance characteristics, and regulatory strategy. Submitted August 2023, accepted January 2025. 
      • Full Qualification Package (FQP) - Provides comprehensive validation data and evidence supporting the tool’s use in regulatory submissions. Submitted Q4  2025. 

Throughout this process, the FDA has provided feedback and suggestions for enhancements. Their input has helped transform an already strong platform into one that’s even more robust, reproducible, scalable, and well-documented. 

The MPA is nearing FDA qualification as a drug development tool. Qualification is a rigorous, multi-step process, for which we have submitted all required documents.

What makes the MPA’s qualification significant?

While the FDA already accepts MPA data, qualification will streamline the regulatory review process. Once the FDA qualifies the MPA, any drug developer can use it in their IND applications “with confidence that the FDA will accept the data” (Roadmap to Reducing Animal Testing in Preclinical Safety Studies). 

The MPA will likely represent several firsts in the New Approach Methodology (NAM) and Drug Development Tool landscape: 

      • The only NAM specificity test with published validation data 
      • The first qualified NAM for specificity testing 
      • On track to be the first NAM qualified through the ISTAND process 
      • On track to be the first NAM qualified as a DDT by the FDA 

For organizations considering qualifying their own drug development tools through ISTAND, we highly recommend it. The experience has been invaluable, and the FDA’s input has genuinely enhanced the platform. 

Looking ahead 

In the coming articles, we’ll share more details about how the MPA works, including the proteins represented in the library, the screening process, and the quality systems that ensure reliable results. We’ll also discuss how MPA data compares to TCR studies and share insights into minimizing false positives and false negatives. 

USPTO Allows Antibody Genus Claims in Patent Enabled by Integral Molecular’s Paratope-PLUS™ CDR-Scanning

Data-Driven Technology Re-establishes a Pathway for Antibody Genus Claims that Meet US Patent Requirements

Philadelphia – Integral Molecular, the industry leader in the discovery and engineering of antibodies against membrane proteins, announces that the United States Patent and Trademark Office (USPTO) has allowed a patent covering a genus of antibodies1 enabled using the company’s Paratope-PLUS® CDR-Scanning technology. The allowed claims protect a lead candidate and a family of structurally related antibodies binding the cancer target GPRC5D that share a common ‘paratope’ structural feature that is responsible for target binding.

The issued patent demonstrates a new pathway for protecting antibody genera using structure-based claims supported by comprehensive experimental data, based on Integral Molecular’s 2025 publication in Nature Biotechnology2. The allowance comes in the wake of the 2023 U.S. Supreme Court ruling in Amgen Inc. v. Sanofi, which emphasized that genus claims must be supported by sufficient disclosure under 35 U.S.C. §112 for enablement and written description. These requirements are met, according to the courts, by defining a common structural feature of the genus (the paratope in this case).

Learn how Paratope-PLUS® CDR-scanning can protect antibody intellectual property

Experimental Data Enables Structure-Based Genus Claims

To generate data enabling genus claims, the Paratope-PLUS platform was used to mutate each residue of the antibody’s CDRs (Complementarity Determining Regions) to all 19 possible alternate amino acids. The resulting experimental dataset identified every variant that retains or even enhances function. CDR-Scanning uses a strategy that mirrors small molecules, claiming a core structural feature (the ‘scaffold’ of a chemical or the ‘paratope’ of an antibody) and all of the permissible variants around that core feature (‘R’ groups of a chemical or amino acid variants of an antibody). The allowed GPRC5D antibody genus claims encompass variants with individual mutations, as well as combinations of mutations that provide permissible levels of binding.

When asked about a path forward for genus claims, Integral Molecular CEO Benjamin Doranz explained, “Big data is transforming both how antibody drugs are being developed and how they are protected in patents. We’ve collaborated with IP experts to create a data package aligned with USPTO guidance to once again provide robust IP protection for antibodies. With today’s high-throughput capabilities, this strategy is now affordable and scalable.”

Paratope-PLUS provides:

  • Laboratory-generated expression and binding data for every antibody variant
  • A genus of structurally related antibodies that meet enablement and written description requirements for broad patent claims
  • Draft claim sets included with the final data report
  • Data describing variants with improved expression, binding, and developability, providing the basis for antibody engineering and novel claims

Benjamin Doranz will discuss the application of CDR-Scanning to antibody intellectual property at the upcoming Life Sciences Patent Network conference on April 29, 2026. He also presented on this strategy in the Resurrecting Antibody Genus Protection webinar, recently hosted by IP Watchdog.

References

  1. U.S. Patent 12,545,726 B1. Compositions and methods related to GPRC5D binding agents and variants thereof.
  2. Banik et al. Redefining antibody patent protection using paratope mapping and CDR-scanning. Nat Biotechnol 43:170–174 (2025).

About Integral Molecular
Integral Molecular (integralmolecular.com) is the industry leader in developing innovative technologies that advance the discovery of therapeutics against difficult protein targets. With 25 years of experience focused on membrane proteins, viruses, and antibodies, Integral Molecular’s technologies have been integrated into the drug discovery pipelines of over 600 biotech and pharmaceutical companies to help discover new therapies for cancer, diabetes, autoimmune disorders, and viral threats such as SARS-CoV-2, Ebola, Zika, and dengue viruses.

Follow Integral Molecular on LinkedIn

Press Contact:
Integral Molecular
Soma Banik, PhD, Director of Public Relations
215-966-6061
info@integralmolecular.com

Are Tissue Cross-Reactivity Studies Sufficient for Biotherapeutic Specificity Testing?

In this article:

This article is part 3 of a series about specificity testing. Be sure to read part 2, about the available tools and when to use them.

Summary 

The short answer is no, tissue cross-reactivity (TCR) studies are not sufficient for biotherapeutic specificity testing. Even though TCR is widely used and has long been recommended by the FDA, it has a long and much-discussed list of limitations. Importantly, TCR results correlate poorly with clinical outcomes, and toxicologists don’t often use TCR data to drive drug development decisions. There is a clear need for a shift to newer specificity testing approaches that are quantitative, objective, validated, and better correlated with patient safety outcomes.

Why are conventional specificity testing methods insufficient?

As described in the previous article in this series, What tools are available for specificity testing during drug development?, tissue cross-reactivity (TCR) studies were the first specificity testing method to be required for biotherapeutic IND submissions beginning in the 1980s. TCR was the best specificity testing tool available at the time, and it quickly became the standard. But as most people familiar with TCR will tell you, the technology has inherent limitations. Importantly, its results correlate poorly with patient safety outcomes.

This article breaks down those limitations, presents some information about how toxicologists use (or don’t use) TCR data, and points to several resources where you can learn more about these topics.

TCR study
TCR is in vitro assay that uses immunohistochemistry (IHC) to reveal antibody binding across a panel of human tissue samples from three individual donors. Results are interpreted by a pathologist, who looks for unexpected off-target binding and previously unknown sites of on-target binding.

What does the literature say about the limitations of TCR studies?

Several published reviews (Cunningham et al., 2021; Li et al., 2020; MacLachlan et al., 2021 ) and case studies (Brennan et al., 2018; Leach et al., 2010) walk through the limitations of using TCR studies for predicting in vivo toxicity and safety.

The following list, pulled from the resources above and our own publications and experiences, summarizes TCR’s most concerning limitations.

  1. TCR cannot identify target proteins. The primary limitation of TCR studies is that they can identify only binding locations; they cannot reveal the identity of specific target or off-target proteins. That means if TCR reveals unexpected binding patterns, the options for follow-up studies to understand the nature of that binding are severely limited. Moreover, on-target tissue staining may provide false reassurance when a target and off-target are expressed within the same tissue or when the off-target is expressed at low levels.
  2. In vivo protein expression is highly variable. Protein expression levels vary within and between tissues, between individuals, and over time—and these levels are difficult to quantify. With TCR, there’s no way to determine whether lack of staining is due to lack of antibody-protein interaction or lack of protein expression.
  3. Processing alters protein conformations. Most TCR tissue samples are fixed or frozen, placed onto glass slides, and processed for staining. These steps can alter proteins’ conformations, potentially leading to false positives and false negatives.
  4. TCR has high background staining levels. Native Fc receptors and endogenous IgG present throughout human tissues frequently cause high background binding, complicating results interpretation.
  5. Scoring is subjective. All TCR results are based on qualitative observations. Trained pathologists score IHC staining results based on their observations and interpretations.
  6. Turnaround is slow. Optimizing the staining protocol and completing TCR studies typically takes 12 weeks or more.
  7. Secreted proteins are excluded. Secreted proteins can be a source of off-target binding, but they are washed off the tissue samples during processing. Thus, TCR cannot reveal target or off-target binding to secreted proteins.
  8. Some protein variations remain untested. Tissue samples from three donors are unlikely to include all possible protein variations present in the general population:
    • Heterocomplex formation and multimer arrangements are often transient or disease specific.
    • Many targets can be expressed as several possible isoforms and have isoform- or disease-specific cellular locations.
    • Post-translational modifications are variable and they can be permanent or transient.
  9. TCR studies are not quantitative. With no quantification, TCR studies cannot be statistically analyzed or tracked for quality control.
  10. TCR studies have never been validated. There are no published analyses of measures such as reproducibility, variability, false-negatives, false-positives, and sensitivity.
  11. TCR studies have never been qualified by the FDA. Although TCR studies are accepted, TCR studies have never formally been qualified by the FDA, who would review the available validation data if it existed.

The long list of limitations shows that while TCR can provide useful information about biotherapeutic binding locations, other tools are needed to better detect and understand off-target binders and predict patient safety outcomes.

Do toxicologists trust TCR for determining specificity?

Given its long list of limitations, it shouldn’t be too surprising that toxicologists don’t trust TCR data. Perhaps the most telling indication of this viewpoint is a set of survey results that captures just how little influence TCR studies have on drug development decisions (MacLachlan et al., 2021). In this survey, industry experts, mostly biotechnology and pharmaceutical toxicologists, answered a series of questions about how they perceive the utility and value of TCR studies.

The results indicate that the vast majority of toxicologists believe TCR results are not predictive of in vivo toxicity, and that TCR results are not actually used in practice to make critical decisions. We encourage you to read the paper.

TCR survey

Cell-based protein arrays fill the gaps

TCR studies leave large information—and trust—gaps. These gaps could be filled by an objective, quantitative, and consistent approach that identifies target proteins and enables statistical analysis between studies.

Fortunately, such tools already exist, and they are increasingly being adopted. Cell-based protein arrays, such as the Membrane Proteome Array (MPA), provide essential information beyond what TCR can deliver.

As this series continues, we’ll share more about cell-based protein arrays and the evolving specificity testing landscape, including what it looks like to qualify a New Approach Methodology (NAM) with the FDA, how MPA and TCR compare in performance, and methods for minimizing false positives and false negatives.

Looking ahead 

In the next article, we’ll dig into how the MPA addresses TCR limitations, and how it is being qualified through the FDA’s ISTAND program.

Integral Molecular Appoints Cheryl Paes as Vice President of Commercial Strategy

Philadelphia – Integral Molecular, the industry leader in the discovery and characterization of antibodies against membrane proteins, announces that Cheryl Paes has joined the company as Vice President of Commercial Strategy. In this role, Paes will lead strategic initiatives to support the continued commercial growth of the company’s technology platforms to serve the biotechnology and pharmaceutical industries.

Paes brings more than 15 years of global experience helping biotechnology and life sciences organizations grow. In her previous roles at Meridian Life Science and Center for Breakthrough Medicines, she led Marketing and Product Management teams focused on understanding customer needs and delivering strategies that helped clients accelerate their pipelines and achieve better outcomes. Earlier in her career, she held commercial leadership roles at Clarivate Analytics and Zimmer Biomet.

“We are excited to welcome Cheryl to Integral Molecular’s leadership team,” said Benjamin Doranz, CEO of Integral Molecular. “Cheryl brings exceptional experience in translating complex scientific platforms into solutions that help our customers. Under Cheryl’s leadership, we will continue to deepen our partnerships, expand access to our technologies, and continue putting customer needs at the center of everything we do.”

Paes joins at a pivotal time as Integral Molecular expands its portfolio of antibody characterization technologies and industry adoption of its platforms continues to increase. This includes the recently launched Paratope-PLUS™ service, built on the company’s comprehensive CDR-Scanning technology, which provides detailed antibody binding analysis to guide antibody engineering and data to support stronger intellectual property.

Integral Molecular also continues to advance its Membrane Proteome Array™ (MPA), a specificity testing platform used to make antibodies, CAR-T cell therapies, and other biotherapeutics safer by identifying off-target interactions. This platform is currently progressing toward FDA qualification, a milestone furthering its adoption as the industry standard for therapeutic specificity testing.

Paes brings a deep understanding of Integral Molecular’s technologies, having previously served in scientific and business advisory roles at the company. Reflecting on the company’s growth and the opportunities ahead, Paes said, “Integral Molecular is at an inflection point. The science is world-class, regulatory approval is imminent, and the biopharma industry is embracing what these technologies make possible. Integral Molecular is uniquely positioned to reshape how partners solve their hardest problems, and I look forward to helping make that happen.”

To learn more about Integral Molecular’s antibody characterization platforms, visit integralmolecular.com.

About Integral Molecular
Integral Molecular (integralmolecular.com) is the industry leader in developing innovative technologies that advance the discovery of therapeutics against difficult protein targets. With 25 years of experience focused on membrane proteins, viruses, and antibodies, Integral Molecular’s technologies have been integrated into the drug discovery pipelines of over 600 biotech and pharmaceutical companies to help discover new therapies for cancer, diabetes, autoimmune disorders, and viral threats such as SARS-CoV-2, Ebola, Zika, and dengue viruses.

Follow Integral Molecular on LinkedIn

Press Contact
Integral Molecular
Soma Banik, PhD, Director of Public Relations
215-966-6061
info@integralmolecular.com

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