Kiromic BioPharma (KRBP) 8-K Other Events

Exhibit 99.1

Bioinformatics to Identify Optimal Solid Tumor Targets and Improve Antigen Selection Maurizio Chiriva Internati,DBSc, PhDs CEO and President, Kiromic BioPharma Associate Professor, The University of Texas, MD Anderson Cancer Center Houston, Texas mchiriva@kiromic.com Confidential Property of Kiromic Biopharma

Forward Looking Statements Confidential Property of Kiromic Biopharma This press release contains forward-looking statements that involve substantial risks and uncertainties. We make such forward-looking statements pursuant to the safe harbor provisions of the U.S. Private Securities Litigation Reform Act, Section 21E of the Securities Exchange Act of 1934, as amended, and other federal securities laws. All statements other than statements of historical facts are forward-looking statements. These statements relate to future events or to our future financial performance and involve known and unknown risks, uncertainties and other factors that may cause our actual results, levels of activity, performance or achievements to be materially different from any future results, levels of activity, performance or achievements expressed or implied by these forward-looking statements. Forward-looking statements include, but are not limited to, statements about: Our goals and strategies; our future business development, financial condition and results of operations; expected changes in our revenue, costs or expenditures; growth of and competition trends in our industry; our expectations regarding demand for, and market acceptance of, our products; our expectations regarding our relationships with investors, institutional funding partners and other parties we collaborate with; fluctuations in general economic and business conditions in the markets in which we operate; including those fluctuations caused by COVID-19; and relevant government policies and regulations relating to our industry. In some cases, you can identify forward-looking statements by terms such as “may,” “could,” “will,” “should,” “would,” “expect,” “plan,” “intend,” “anticipate,” “believe,” “estimate,” “predict,” “potential,” “project” or “continue” or the negative of these terms or other comparable terminology. These statements are only predictions. You should not place undue reliance on forward-looking statements because they involve known and unknown risks, uncertainties and other factors, which are, in some cases, beyond our control and which could materially affect results. Factors that may cause actual results to differ materially from current expectations include, among other things, those listed under the heading “Risk Factors” included in our Registration Statement on Form S-1 (file no. 333-257427) , originally filed with the Securities and Exchange Commission (SEC) on June 25, 2021, and elsewhere in this press release. If one or more of these risks or uncertainties occur, or if our underlying assumptions prove to be incorrect, actual events or results may vary significantly from those implied or projected by the forward-looking statements. No forward-looking statement is a guarantee of future performance. The forward-looking statements made in this report relate only to events or information as of the date on which the statements are made in this report. Except as expressly required by the federal securities laws, there is no undertaking to publicly update or revise any forward-looking statements, whether as a result of new information, future events, changed circumstances or any other reason.

Outline Confidential Property of Kiromic Biopharma 3 1. AI 2. Discuss what is the Cd19 equivalent in solid tumor (Isomeso) 3. Review the clinical potential of HER2, MAC3,, Mage3, Mage 4 4. Best in Class bioinformatics platforms to identify safe targets

Confidential Property of Kiromic Biopharma

AI AI extracts information from SingleCellRNAseq, and produces prediction models of the Tumor Environment Confidential Property of Kiromic Biopharma

Genomics/ Transcriptomics Copy number abberrations (CNAs) Messenger RNA (mRNA) Clinical Data Proteomics AI in immunotherapy (Level 1): integrating OMICs from biospecimen and TME Simidijevskim, Lio, Front Gen 2019 Artificial Neural Networks/Variational autoencoders, can combine different information levels into different architectures for a deep analysis and comparison with respect to specific data features Prediction of Protein Protein interactions (PPI), pivotal for determining the antigen context Kong, Dehmer, Front Gen. 2020 Protein sequences patient biospecimen: heterogeneous cancer data output Principal Component Analysis (PCA) FCTP-WSRC (Protein codifier) SNPs, New Antigens, Epitopes Selected antigen peptides Single Cell RNA sequencing DNA Methylation AI will plan personalized target therapies, based on the TCR sequencing, by SCRNA seq + integration of different OMICS Mosch Front Gen. 2019 AI TME Analyses of cytokines: i.e.: IL- 1, IL-6 and TGFβ PCA Features identification Characterization of the patient’s TME, by Single Cell RNA seq of the tumor specimen, and identification of the major features through AI. Confidential Property of Kiromic Biopharma

Genomics Transcriptomics Proteomics Metabolomics Cancer biospecimens Omics Digital pathology Social media Hospital/Institute AI infosphere/BigData Food preferences Life quality Clinical info Habits PERSONALIZED THERAPY Confidential Property of Kiromic Biopharma AI in immunotherapy (Level 2) Drugs

Number of employees W ee k s 1 day Discovery: 1 Target = 1 Cancer Vs A.I. $$ Humans ~$$$$ 1 Year 1 158 1 Year CencerSplice Confidential Property of Kiromic Biopharma

Cancer Immune peptides Databases Cancer Genome Atlas Public Databases Public Databases Public Databases R-Epitope (Epitope Selection) Cancer Splice (Iso-form Selection and 3D Visualization) iCloud Isoform Target prediction Target Validation (Algorithm and Wet Lab Validation) Cancer Cand i da t e s Diamond AI predictions and validations reduce development costs by eliminating targets that will ultimately fail laboratory analysis Laboratory studies are then performed to confirm the validity of the AI selected target Diamond Clinical AI models can be used to continually improve identification of patients mostly likely to respond to treatment Diamond AI drives discovery by sifting through billions of data points to identify cancer specific immunotherapy targets Diamond Donor AI models use demographics, cytometry data, and sequencing to identify the best targets - improving the final product. Clinical Trials The Difference - Diamond AITM Target Discovery Engine DiamondTM A.I. target discovery engine powers innovation, speeds development and reduces costs 1 2 3 4 5 <5yrs CencerSplice Confidential Property of Kiromic Biopharma

Confidential Property of Kiromic Biopharma 10 ISO-Mesothelin • Mesothelin is a GPI-anchored cell surface glycoprotein that is overexpressed in about 30% of solid tumors. Given its limited expression in normal mesothelial cells and high expression in the majority of mesothelioma, ovarian and pancreatic cancers, mesothelin- directed therapy has been intensively studied in preclinical and clinical settings. • Based on our proprietary diamond AI platform, we found MSLN isoform 2 (“IsoMSLN”) is specifically expressed in mesothelioma, ovarian cancers and pancreatic cancer. AACR 2021

Confidential Property of Kiromic Biopharma 14 • Large, heterogeneous with various method of administration landscape Cancer biomarker landscape Tumor heterogeneity • Different cancers have different targetable antigens and express them at different levels • Not all tumor cells in a tumor mass are positive for the same target • This leads to different cancer biomarker Biomarker antigens have a variety of method of administration • The therapeutic approach needs to be tailored to the [tumor] localisation of the target • The main cancer biomarkers used in the clinical practice are still dominated by PD-1, Her2, PSA, CD19, and hormone receptors • This limits the number of targetable indications and the general applicability of related immunotherapies Various biomarker method of administration Discovery platform needed to identify the variety of biomarker antigens • Past approaches do not target most of the cancer indications and do not show the expected clinical efficacy • Most single-analyte biomarkers have been generated and studied because of a pre- conceived biological association between them and the associated disease • Time consuming approach

Biomarker discovery platform landscape Oncology & Other Diseases Old “common” targets products: PD1/PDL1, Her2, MART, MUC-1, CA125, NY-ESO-1, CD20, CD19 Immune checkpoint inhibitors (~360 companies) Vaccines (>30 companies) T-cell therapies (~30 companies) CAR-T therapies (~60 companies) Personalis (exome analysis for neoantigens) Pure-MHC Empirical epitope discovery Ab ther. Immatics Neoantigens T-cell ther. Gritstone Neoantigens Virus-vaccine (with ImmuneDesign) Kiromic Diamond AI ✓ DC ther. ✓ Vaccines ✓ Oral Vaccines ✓ T-cell ther. ✓ mAb ✓ CART ✓ TCRT ✓ Companion tests ImmuneDesign Virus-mediated delivery to DC in vivo Patient and tumor specific expression profile Patient’s medical history will be factored in to: 1. Maximize drug potency 2. Minimize harmful side effects ⚫A myriad of open access and proprietary database are at Kiromic’s disposal ⚫“Kiromic only” training set and library T-cell CART GDT therapies (~5 companies) CAR-NK therapies (> 60 companies) Vaccines Oral (>2 companies) Confidential Property of Kiromic Biopharma 16

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Kiromic Diamond AI engine identified a “tumor-specific” MSLN isoform Soluble form Major form Tumor-specific isoform Figure. Bioinformatic analysis for the detection of cancer-associated isoforms. A) cancer tissues distribution of the IsoMSLN transcripts per million reads (TPM) values is presented, showing the greatest upregulation in ovarian cancer (OC) followed by malignant pleural mesothelioma (MPM). B) Multi sequence alignment of the transcript variants protein products. Red sequence= canonical form, blue highlighted sequence= cancer-associated isoform, black sequences= protein products of minor transcripts with low TPM values. AACR 2021 Confidential Property of Kiromic Biopharma 14

Proteomics Figure. The peptide is a fragment of the unique peptide of ISOMSLN was detected in 71% of OV tumor samples and in 61% of adjacent normal samples. The peptide GHEMSPQVATLIDR, which is not found in IsoMSLN but it is found in all the protein translated from to the other MSLN transcripts, was also detected. This peptide was found in 100 % of normal and 100% of tumor samples. The box plots illustrates the distribution of RPLPQVATLIDR, the IsoMSLN peptide, in tumor samples and adjacent normal. AACR 2021 Confidential Property of Kiromic Biopharma 15

Results – IsoMSLN is protein is expressed in Solid tumors tissues NORMAL OVARIAN TISSUE NORMAL PANCREAS TISSUE NORMAL MESO-LUNG HIGH GRADE SROUS CARCINOMA PANCREATIC ADENOCARCINOMA PRIMARY MESOTHELIOMA Figure. Histopathology staining of tumor cell line and primary tumor tissue array by anti-IsoMSLN-specific antibodies.A) Validation of anti-IsoMSLN antibodies for IHC staining in Lenti-X 293T cells with or without IsoMSLN expression. Anti- pan- MSLN antibody (5B2) is used as positive control. Tumor cells from cell culture were harvested and embed in HistoGel (Thermo Scientific).B) anti-IsoMSLN antibody IHC staining in primary tissues (50x magnification) from ovarian cancer tissue section.C) anti-IsoMSLN antibody IHC staining in primary tissues (50x magnification) from ovarian cancer tissue, pancreatic adenocarcinoma tissue, primary mesothelioma tissue.D) Summary table of the IHC findings. AACR2021 1 1 C 1 1 5B 2 293T- IsoMSLN 293T AHELA NCI H226 B 1 B 6 Confidential Property of Kiromic Biopharma We selected the 11C11 antibody clone for further development, due to its specificity of IsoMSLN and higher affinity compared to the 1B6 clone.

The MAC antigen family: MAC-1 The ITGAM gene (MAC-1) encodes the integrin alpha M chain. Integrins are heterodimeric integral membrane proteins composed of an alpha chain and a beta chain. This I-domain containing alpha integrin combines with the beta 2 chain (ITGB2) to form a leukocyte-specific integrin referred to as macrophage receptor 1 ('Mac-1'), or inactivated-C3b (iC3b) receptor 3 ('CR3’). The alpha M beta 2 integrin is important in the adherence of neutrophils and monocytes to stimulated endothelium, and also in the phagocytosis of complement coated particles. Multiple transcript variants encoding different isoforms have been found for this gene. ITGAM Facilitates transmigration of leukocytes across vascular endothelia, intercellular adhesion Cancers 2021, 13, 77. https://doi.org/10.3390/ cancers13010077 https://www.ncbi.nlm.nih.gov/gene/3684 Confidential Property of Kiromic Biopharma

• Chang MH, Karageorgos LE, Meikle PJ (2003). "CD107a (LAMP-1) and CD107b (LAMP-2)". Journal of Biological Regulators and Homeostatic Agents. 16 (2): 147–51. PMID 12144129 • Journal for ImmunoTherapy of Cancer 2020;8:e000258 C. o d n o fii d : e 1 n 0 ti. a 1 l 1 P 3 ro6 p / e jir t t c y - o 2 f 0 K 1 ir9 o - m 00ic0 B 2 io5 p 8 h . arma • Lysosome-associated membrane protein 2 (LAMP2), called also MAC-3 or CD107b (Cluster of Differentiation 107b, is one of the lysosome-associated membrane glycoproteins. This glycoprotein provides selectins with carbohydrate ligands. It may play a role in tumor cell metastasis. • It may also function in the protection, maintenance, and adhesion of the lysosome. • Alternative splicing of the gene produces three variants - LAMP-2A, LAMP-2B and LAMP-2C.[5] LAMP-2A is the receptor for chaperone-mediated autophagy. • LAMP-2B is associated with Danon disease. • Alternative antigens trafficking use lysosome-associated membrane protein 1 (LAMP) domain to enhance vaccine efficacy against HER2 and other model antigens in both in vitro and in vivo studies. • Inclusion of LAMP protein in plasmid vaccines effectively trafficked antigens to endo-lysosomal compartments, resulting in enhanced major histocompatibility complex (MHC) class I and II presentation. The MAC antigen family: MAC-3

Moffitt et al. identified two different stromal subtypes, normal and activated based on different genes expression. The first subtype is characterized by high expression of genes that are associated with macrophages, such as integrins (ITGAM) and chemokine (C-C motif) ligand (CCL) 13/18. (Nature Genetics volume 47, pages1168–1178 (2015) Despite the fact that pancreatic cancer is a non-immunogenic cancer, a robust amount of infiltrate immunogenic cells, such as tumor-associated macrophages (TAMs), myeloid derived suppressor cells (MDSCs) and neutrophils, has been identified (https://doi.org/10.1177/1758835918816281) Confidential Property of Kiromic Biopharma Identification of MAC-1 (ITGAM) in pancreatic adenocarcinoma stroma (PAC) https://doi.org/10.1016/j.ctrv.2020.102016

• The Melanoma Antigen Gene (MAGE) protein family is a large, highly conserved group of proteins that share a common MAGE homology domain. • Many MAGE proteins are restricted in expression to reproductive tissues but are aberrantly expressed in a wide-variety of cancer types. • Originally discovered as antigens on tumor cells and developed as cancer immunotherapy targets, recent literature suggests a more prominent role for MAGEs in driving tumorigenesis. • They are of particular interest for cancer immunotherapy because of their strict tumoral specificity and because they are shared by many tumors. Curr Opin Cell Biol. 2015 Dec; 37: 1–8. doi: 10.1016/j.ceb.2015.08.002 Summary of known biochemical and cellular functions of MAGEs: altering the subcellular localikzation of E3, binding ubiquinated substrates, and/or processing non-Ub functions, like transcription Confidential Property of Kiromic Biopharma The MAGE family

Antigenic peptide EADPTGHSY encoded by MAGE-A1 and known to be presented by HLA-A1 is currently being used in therapeutic vaccination trials. Literature has reported that a cytotoxic T-lymphocyte (CTL) clone, which is restricted by HLA-B35, recognizes the same peptide and, importantly, lyses HLA-B35 tumor cells expressing MAGE-A1. This peptide can be presented to CTL by both HLA-B*3501 and HLA-B*3503 molecules, which are expressed by approximately 19% of Caucasians. These results infer that the current clinical use of peptide EADPTGHSY can now be extended to HLA-B35 patients. MAGE-3.A1 peptide vaccine may stimulate the immune system to mount a cytotoxic T-cell (CTL) response against tumor cells expressing MAGE-3, resulting in tumor cell lysis. MAGE-3, a tumor-associated antigen (TAA), is overexpressed by a variety of cancer cell types. Luiten RM et al: Tissue Antigens 2000 Jul;56(1):77-81. doi: 10.1034/j.1399-0039.2000.560110.x Confidential Property of Kiromic Biopharma MAGE-A1 in melanoma immunotherapy

MAGE-3.A1 in melanoma immunotherapy A cancer vaccine comprising synthetic peptides derived from human melanoma antigen A1 (MAGE-A1), human melanoma antigen A3 (MAGE-A3) and cancer-testis antigen NY-ESO-1, was developed. The vaccine has potential immunostimulating and antineoplastic activities. Upon administration, MAGE-A1/MAGE-A3/NY-ESO-1 peptides vaccine may stimulate the immune system to mount a cytotoxic T-cell (CTL) response against tumor cells expressing MAGE-A1, MAGE-A3 and NY-ESO-1, resulting in tumor cell lysis. The MAGE-A1, MAGE-A3, and NY-ESO-1 tumor-associated antigens (TAAS) are overexpressed by a variety of cancer cell types. The MAGE-3.A1 peptide used is EVDPIGHLY Int J Cancer. 1999 Jan 18;80(2):219-30. doi: 10.1002/(sici)1097-0215(19990118)80:2<219::aid-ijc10>3.0.co;2-s Confidential Property of Kiromic Biopharma

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